A term that has gained acclaim in recent years, big data refers to using data analytics to extract intelligent value from information. Big data encompasses massive amounts of data that a company can use in many ways – and in real time. This information lends insight into how top data companies can improve their operations and better understand customer behaviors and needs.

Let’s take a look at the top big data companies in 2023.

Table of Contents: 

• Top Big Data Companies
  
• What Exactly Does a Big Data Company Do?
• Why Do Organizations Need a Big Data Solution?

Top Big Data Companies

Microsoft

This U.S.-based company was founded in 1975 and is headquartered in Washington state. Microsoft’s big data strategy includes a partnership with Hortonworks (now merged with Cloudera), providing an HDInsight tool for analyzing massive amounts of both structured and unstructured data on Hortonworks’ data platform (HDP).

Big Data Expertise

Microsoft brings big data to billions of people by providing easy access to all data with the help of its Azure cloud platform. The big-name company also gives IT a complete data platform to scale insights across their organizations confidently.

Top Industries That Use Microsoft

• Energy
• Retail
• Gaming
• Banking and finance
• Sports and media
• Government
• Manufacturing

Microsoft’s Solutions

Microsoft has three solutions based on HDP:

• HDInsight
• HDP for Windows
• Microsoft Analytics Platform System

Amazon AWS

Amazon was founded in 1994 with its headquarters in Washington. The company is best known for its cloud-based platform. However, this tech giant also offers big data products, with its main product being the Hadoop-based Elastic MapReduce.

Big Data Expertise

Big data analytics applications can be built and deployed quickly using Amazon Web Services, virtually, if needed. AWS helps to collect, analyze, store processes, and visualize big data on the cloud.

Top Industries That Use Amazon AWS

• Advertising and marketing
• Aerospace
• Automotive
• Games
• Education
• Retail
• Government
• Media

Amazon’s Solutions 

Amazon’s solutions include:

• Amazon EMR
• Amazon Elasticsearch Service
• Amazon Athena
• Amazon Kinesis Firehose
• Amazon Kinesis Streams
• Amazon Kinesis Analytics
• Business intelligence (BI)
• Artificial intelligence (AI)
• Internet of Things (IoT)
• Data movement

Google

This California-native company was founded in 1998 and has employees and offices worldwide. Google provides integrated and end-to-end big data solutions based on the tech giant’s innovation. It helps organizations capture, process, analyze, and transfer data in a single platform.

Big Data Expertise

Google is expanding its big data analytics with BigQuery. This cloud-based analytics platform quickly analyzes large quantities of data. In addition, BigQuery is a serverless, fully managed, and low-cost enterprise data warehouse.

Top Industries That Use Google

• Retail
• Finance
• Healthcare
• Gaming
• Media
• Manufacturing
• Supply chain logistics
• Government
• Education

Google’s Solutions

Google’s cloud solutions offer application modernization, AI, application programming interfaces (APIs), databases, security, smart analytics, infrastructure modernization, and productivity and collaboration.

• Cloud DataFlow
• Cloud Dataproc
• Cloud Datalab

IBM

IBM is an American company headquartered in New York. Founded in 1911, IBM has remained relevant with modern technologies as a top big data company with solutions providing features such as storage, data management, and data analysis.

Big Data Expertise

IBM’s big data solutions are designed to process massive amounts of data to gain business insights and to capture, analyze, and manage any structured and unstructured data. IBM, one of the largest companies worldwide, includes BigInsights and Hadoop as a service in its IBM SoftLayer cloud infrastructure.

Top Industries That Use IBM

• Aerospace and defense
• Automotive
• Banking and finance
• Government
• Education
• Manufacturing
• Entertainment
• Retail
• Travel

IBM’s Solutions

• Hadoop System
• Stream Computing
• IBM BigInsights for Apache Hadoop
• IBM BigInsights
• IBM SoftLayer cloud infrastructure
• IBM Streams for the Internet of Things

HPE

HPE was founded in 2015 in Palo Alto, California, when the original Hewlett-Packard company split into two companies. HPE works in servers, storage, networking, containerization software and consulting, and support. Among HPE’s big data offerings is HPE GreenLake.

Big Data Expertise

GreenLake is designed as an as-a-service solution to offer faster data mining by lowering the challenges and costs of the Hadoop platform. In addition, it provides software-hardware combinations for in-house installation and tools to monitor and manage data activity.

Top Industries That Use HPE

• Manufacturing
• Telecommunications
• Health and life sciences
• Financial services
• Public sector
• Small and midsize businesses
• Media and entertainment
• Service providers

HPE’s Solutions

• Aruba ESP (Edge Services Platform)
• HPE Moonshot
• HPE Apollo 4000 purpose-built server
• HPE ConvergedSystem
• HPE 3PAR StoreServ 20000
• HAVEn, a big-data platform

Oracle

Founded in 1977, Oracle is a multinational technology corporation headquartered in Austin, Texas. This global tech company designs, manufactures, and sells software and hardware products as well as services that complement them. Oracle has the distinction of being one of the world’s largest software companies based on revenue.

Big Data Expertise

Oracle is a top big data company known for its flagship database. In addition, Oracle offers fully integrated cloud applications and platform services. The company has business solutions that leverage big data analytics and applications to provide insight into logistics and fraud.

Top Industries That Use Oracle

• Banking
• Healthcare
• Manufacturing
• Retail
• U.S. government

Oracle’s Solutions

• Oracle Big Data Preparation Cloud Services
• Oracle Big Data Appliance
• Oracle Big Data Discovery Cloud Services
• Data Visualization Cloud Service

Dell EMC

Founded in 1984, this Austin-based company sold only hardware until 2009. Now, people recognize the name Dell for its PCs, servers, and software. Dell is also well-known for how it handles supply chains and e-commerce.

Big Data Expertise

In March 2014, Dell acquired StatSoft to help bolster its big data solutions. Dell EMC helps small and large businesses store, analyze, and protect their data. In addition, it allows enterprises to better understand customer behaviors and risks.

Top Industries That Use Dell EMC

• Media and entertainment
• U.S. federal government
• Energy
• Healthcare
• Education
• Retail

Dell EMC Solutions

• PowerEdge for Hadoop
• Boomi
• Isilon
• ECS

SAP

SAP is a business software company founded in 1972. This large provider of enterprise application software has headquarters in Walldorf, Germany, and has 110 million cloud subscribers.

Big Data Expertise

SAP’s primary big data tool is the HANA-in-memory relational database. It integrates with Hadoop, allowing organizations to turn massive amounts of big data into real-time insights. In addition, SAP’s solutions use automated data preparation and deployment of predictive modeling. As a result, it can analyze massive amounts of data and proactively respond to potential threats.

Top Industries That Use SAP

• Retail
• Government
• Manufacturing
• Entertainment
• Media

SAP’s Solutions

• SAP Predictive Analytics
• SAP IQ, formerly known as Sybase IQ
• SAP BusinessObjects BI

Splunk Enterprise

Splunk is a cloud computing company founded in 2003 and based in San Francisco, California. It started as a log analysis tool in 2003 but has expanded its focus to machine data analytics, which make it possible for the data or information to be usable by anyone.

Big Data Expertise

Splunk boasts a wide range of expertise that helps mitigate security risks, maintain infrastructures’ operational health and security, and transform IT, security, and business operations through data analytics. Using Splunk big data, users can study customer data and search, explore, and visualize data in one place.

Top Industries That Use Splunk

• Aerospace and defense
• Communications
• Energy and utilities
• Financial services
• Healthcare
• Higher education
• Manufacturing
• Nonprofits
• Online services
• Public sector
• Retail

Splunk’s Solutions

• Splunk Analytics for Hadoop
• Splunk ODBC Driver
• Splunk DB Connect

Teradata

Founded in 1974 with headquarters in Dayton, Ohio, Teradata provides an analytic data platform, marketing, consulting services, and analytics application.

Big Data Expertise

Teradata’s big data solutions help organizations to gain an advantage with data by using big data applications, such as Teradata QueryGrid, Teradata Listener, Teradata Unity, and Teradata Viewpoint.

Top Industries That Use Teradata

• Automotive
• Energy and natural resources
• Financial services
• Government
• Healthcare
• Manufacturing
• Media and entertainment
• Retail
• Travel and transportation
• Utilities

Teradata’s Solutions

• Integrated Data Warehouse
• Kylo
• Aster Big Analytics Appliance
• Data Mart Appliance

VMware

Founded in 1998 and headquartered in Palo Alto, California, VMware is well-known for its cloud computing and virtualization, but lately, it is becoming a big player in big data. Since 2005, this computer software company has acquired multiple companies, helping to improve its cybersecurity, digital transformation, and automation and configuration of management software.

Big Data Expertise

VMware big data solutions tout simple, flexible, cost-effective, agile, and secure products. VMware vSphere Big Data Extension enables companies to deploy, manage, and control deployments. Further, VMware supports Hadoop distributions which include Apache, Hortonworks, and MapR. The company’s virtualization of big data enables simpler big data infrastructure management while delivering results quickly and cost-effectively.

Top Industries That Use VMware

• Communications service providers
• U.S. federal government
• Finance
• Healthcare
• State and local government

VMware’s Solutions

• VMware vSphere Big Data Extensions (BDE) Native app platform
• Cloud infrastructure
• Cloud management
• Edge infrastructure
• Networking security

Cogito

Founded in 2007 with headquarters in Boston, Massachusetts, Cogito aims to develop an AI platform and behavioral models to automatically interpret human communication and detect psychological states. It uses AI to help companies and people be more productive.

Big Data Expertise

Cogito uses behavioral analytics technology, including analysis of customer interactions, ranging from online to human voice analysis, to help improve communications with customers. Cogito’s software evaluates behavioral voice signatures to provide live conversation coaching for agents. There is a real-time measure of customer experience for every call.

Top Industries That Use Cogito

• Finance
• Insurance
• Healthcare
• Travel
• Retail

Cogito’s Solutions

• Cogito Dialog

iTechArt

Since 2002, iTechArt has provided fully dedicated engineering teams and custom software solutions. The company has dedicated teams leveraging big data development services to help clients manage data quickly. Headquartered in New York, iTechArt has been a trusted partner for growing startups and innovative companies.

Big Data Expertise

iTechArt’s big data services encompass every aspect of data engineering implementation, so they can power company-wide business transformations. iTechArt will gather, process, clean, and transform data for automated, streamlined business analysis.

Companies can also streamline existing data and integrate it with third-party systems to make a powerful, big-data solution. For example, data can be converted into user-friendly graphs, maps, and charts.

Top Industries That Use iTechArt

• Fintech
• Marketing and adtech
• Healthtech
• E-commerce
• Edtech
• Real estate
• Fitness and wellness
• Food and beverage
• iGaming
• Nonprofit

iTechArt’s Solutions

• Artificial neural networks
• AI algorithms and applications
• Natural language processing (NLP)
• IoT solution development
• Big data cluster management
• Parallel computing
• Graphics processing unit (GPU) processing
• Data governance
• Real-time and batch processing

Innowise Group

Founded in 2007, Innowise is a software development company that seeks to develop innovative technologies to serve the information technology sector in several key big data sectors. 

Big Data Expertise

Innowise Group provides big data development services that enhance companies’ productivity and efficiency, using cutting-edge modern technologies. Its big data solutions handle massive volumes of information and extract valuable insights to help make better decisions. Innowise builds data lakes; sets up extract, transform, load (ETL) and extract, load, transform (ELT) processes; and develops big data applications.

Top Industries That Use Innowise

• Healthcare and life sciences
• Finance, banking, and insurance
• E-commerce and retail
• Hi-Tech
• Education
• Telecommunications
• Automotive
• Media and entertainment
• Construction and real estate
• Energy and utilities
• Enterprise
• Public services
• Logistics and transportation
• Marketing and advertising
• Manufacturing

Innowise’s Solutions

• Big Data Consulting
• Big Data Development
• Big Data Analytics
• Big Data Visualization
• Big Data Mining
• Big Data Automation

Oxagile

Founded in 2005, with headquarters in New York, Oxagile has over 1 billion users. Oxagile made the journey from a startup to a mature software provider quickly and now boasts domain solutions for various industries.

Big Data Expertise

Oxagile will help businesses choose the right tools and implement a unified BI solution to help create a suitable, approachable, and scalable solution for any digital company.

Top Industries That Use Oxagile

• Media and entertainment
• Advertising
• Software and IT services
• Security and public safety
• Healthcare technology
• Sports and fitness
• Retail
• Finance and banking

Oxagile’s Solutions

• Data engineering
• Data analysis and visualization
• Data and pipeline migration
• Apache Hadoop
• Apache Spark
• Snowflake Data Cloud
• AWS integration

Integrate.io

Integrate.io is headquartered in San Francisco, California, and was founded in 2012. The company specializes in big data; software as a service (SaaS); and data management, processing, and integration. Calling themselves the “No-Code Data Pipeline Platform,” Integrate.io’s ETL and reverse ETL, ELT and change data capture (CDC), API generation, and observability platform helps companies evolve along their data journey.

Big Data Expertise

Integrate.io’s big data processing cloud service provides immediate results to businesses with its cloud-based data integration, ETL, and ELT platform. Able to streamline data processing, Integrate.io brings all data sources into one space.

Through this platform, organizations can process and prepare data for analysis on the cloud. Integrate.io allows businesses to benefit from big data company opportunities without investing in hardware, software, or data professionals.

Top Industries That Use Integrate.io

• E-commerce
• SaaS
• Media and entertainment
• Travel
• E-learning
• Healthcare

Integrate.io’s Solutions

• ETL and reverse ETL
• ELT and CDC
• API generation
• Data warehouse analytics
• Customer 360
• Data security
• Data ingestion
• Business intelligence

RightData

Founded in 2016 and headquartered in Atlanta, Georgia, RightData is a trusted total software platform that empowers end-to-end capabilities for current data, analytics, and machine learning needs. Its vision is to enable companies with end-to-end self-service tools that accelerate value creation from data, so they can arrive at the best decisions at the lowest cost in the quickest time.

Big Data Expertise

The combination of data integration Dextrus software and RDt data quality provides a comprehensive DataOps data software approach that unifies data scientists and business users. Dextrus accelerates the data ingestion, transformation, cleansing, and delivery of vast volumes of batch, streaming, and real-time data from diverse sources.

Moreover, RightData’s no-code product RDt tests, reconciles, and validates for integrity at every stage of the data journey.

Top Industries That Use RightData

• Healthcare
• Retail
• E-commerce and retail
• Hi-Tech
• Telecommunications
• Finance

RightData’s Solutions

• Dextrus
• RDt

ScienceSoft

Founded in 1989, ScienceSoft is a provider of IT consulting and software development services. ScienceSoft started as a small AI product company and switched to IT services in 2002. It aims to help non-IT organizations and software product companies improve business performance.

Big Data Expertise

ScienceSoft has been at the forefront of data management and AI since its beginnings. It works with mid- to large-sized businesses to build big data platforms and dedicated big data solutions.

Top Industries That Use ScienceSoft

• Healthcare
• Manufacturing
• Professional services
• Banking and financial services
• Insurance
• Retail
• Transportation and logistics
• Telecommunications
• Oil and gas

ScienceSoft’s Solutions

• CRM
• Marketing and advertising
• Human resources
• E-learning
• Document management
• Supply chain management
• Fleet management
• Kiosk software
• ERP
• Operations management
• Financial management
• Asset management
• Project management
• Data analytics
• E-commerce
• Web portals
• CMS

InData Labs

Located in Cyprus, Singapore, InData Labs was founded in 2014 by a video game industry veteran, bringing years of experience analyzing big data. InData Labs seeks to enable clients to get valuable insights into data, automate repetitive tasks, enhance performance, and add AI-driven features.

Big Data Expertise

InData’s big data expertise lies in its ability to build data lakes and warehouses, implement cutting-edge analytics, and develop big data applications. In addition, it has expertise in AWS and Azure.

Top Industries That Use InData Labs

• Healthcare and pharmaceuticals
• Games and entertainment
• Sports and wellness
• Automotive
• Fintech
• E-commerce
• Logistics
• Retail

InData Labs’s Solutions

• ​​Modern data architecture
• Data engineering services
• Big data analytics
• Data warehouse
• BI and data visualizations

TIBCO

TIBCO Software, a Cloud Software Group business unit, has its headquarters in Palo Alto, California. Founded in 1997, TIBCO’s then-revolutionary software enabled communication within the finance industry to occur in real time.

Big Data Expertise

TIBCO’s Spotfire excels at performing visual analytics. While Statistica is for moving data through complex pipelines. Alpine Data Labs was acquired by TIBCO, and the company’s advanced analytics interface on Apache Hadoop provides a visual environment for building analytics workflow and predictive models.

Top Industries That Use TIBCO

• Banking
• Credit union
• Energy
• Government
• Healthcare
• Insurance
• Law enforcement
• Manufacturing
• Retail
• Telecommunications
• Travel and transportation

TIBCO’s Solutions

• Spotfire
• Data science software

Striim

Striim was founded in 2012 and has headquarters in Palo Alto, California. This software developer focuses on combining streaming integration and intelligence in one platform.

Big Data Expertise

Striim’s streaming analytics platform connects clouds, data, and applications with unprecedented speed and simplicity. Striim is known for integrating a wide variety of data sources, such as transaction data capture events, log files, and IoT sensor data, using real-time correlation across multiple streams.

Top Industries That Use Striim

• Healthcare
• Logistic
• Retail
• Financial services
• Telecommunications

Striim’s Solutions

• Data modernization
• Real-time operations
• Data fabric and data mesh technology
• Digital customer experience
• Real-time analytics
• AWS
• Google Cloud
• Microsoft Azure
• Databricks
• Snowflake

Talend

This San Mateo-based company was founded in 2005 and is an open-source platform for software integration. Talend is a leader in data integration and uses its expertise to change the way the world makes big data decisions.

Big Data Expertise

Talend Data Fabric currently is the only platform that combines an extensive range of data integration and governance capabilities to manage corporate information.

Top Industries That Use Talend

• Financial services
• Healthcare
• Government
• Retail
• Telecommunications

Talend’s Solutions

• Talend Trust Score

What Exactly Does a Big Data Company Do? 

A big data company works with large amounts of data from various sources, including email, mobile apps, social networks, customer databases, and internet clickstream logs. Because this information can be used to define and drive best practice decisions across industries, it’s no surprise that a company will need a way to analyze it.

Most big data companies specialize in finance, healthcare, retail, and manufacturing, so one can imagine the massive amount of information within its framework. Yet it’s about something other than how huge their data information is; it’s about what companies do with this large amount of data.

Therefore, a company may use predictive analytics tools and artificial intelligence to help companies better understand information, such as historical data, while improving future business ventures.

Why Do Organizations Need a Big Data Solution? 

Big data can help organizations make better business decisions. With massive amounts of data at their disposal, big data companies need solutions to help parse all of the information into usable datasets. Big data helps businesses gain more insight into their customers, which in turn helps them stay ahead of the competition.

Big data can also help analyze risks and real-time business decision-making. Therefore, the more data companies have on their users, the better their business solutions can be.

For most businesses, employing a big data strategy comes from the need to analyze massive amounts of data to understand business insights quickly and holistically. Using information from technologies including data management applications, analytics, and cloud-based data mining tools, insights can be translated into familiar tools such as excel sheets, making it easier for professionals with non-technical backgrounds to analyze data and make better business decisions.

A quick LinkedIn search for the job title data scientist shows over 200,000 results. Clearly, there’s a data science talent shortage in 2023 – particularly for those pros who have data science certifications. 

The following list highlights top-tier companies that pay the most, have the best perks, and are well-known as being generally great places to work. If you’re in the job market for a data scientist role, this list of top data science companies should help you narrow your search.

Jump ahead:

• Top Companies Hiring Data Scientist
• What is the Average Salary of a Data Scientist?
• What Should You Consider When Choosing a Company as a Data Scientist?
• How We Selected the Top Companies Hiring Data Scientists
• Working at the Best Companies for Data Scientists

Top Companies Hiring Data Scientists

1. Deloitte

Deloitte is a global professional services leader specializing in several financial and technical implementation solutions. Its core focus includes tax, consulting, audit and assurance, private company services, mergers and acquisitions, risk and financial advisory, analytics, and cloud.

Why Deloitte Is Investing in Data Science

Deloitte is focused on data science goals and embraces a data-driven mindset. It believes in developing a data management plan and changing the organizational mindset to embrace more objective and data-backed decisions.

Positions Available

• Senior data scientist
• Data science consultant
• Junior data scientist

Average Data Scientist Salary at Deloitte

The estimated total pay for a data scientist at Deloitte is $111,439 per year.

Notable Benefits

• Well-being subsidy.
• Thank It Forward recognition program.
• Live well counseling support.
• Student loan refinancing.
• Military leave.

2. Dice

Dice’s tech-focused career marketplace enables direct, meaningful connections between recruiters and technologists. Dice is a DHI brand that provides AI-powered software products and online tools for technology-focused roles.

Why Dice Is Investing in Data Science

Dice is transforming electric grid technology to support smart grids. As a result, the data platform products are being continuously enhanced, and the number of BI solutions is growing rapidly. Additionally, teams are responsible for charting the path for data strategy within their organizations.

Positions Available Include

• Data scientist
• Data scientist UDF (user-defined function)
• Customer relationship management (CRM) and segmentation analyst

Average Data Scientist Salary at Dice

The estimated total pay for a data scientist at Dice is $101,776 per year.

Notable Benefits

• Unlimited holidays with no cap on PTO.
• Health, dental, and vision plans.
• DICE Development, a training and support program to help career progression.

3. PwC Accounting and Professional Services

PwC is a global professional services firm focusing on assurance, advisory, and tax services. Other core areas include cloud and digital; deals; cybersecurity and privacy; governance and boards; risk; transformation; and environmental, social, and governance (ESG).

Why PwC Is Investing in Data Science

PwC aims to advise better companies that face increasing inspections from investors on data privacy, sustainability, and diversity issues. The company strives to consistently deliver innovative work that builds trust and provides sustained outcomes.

Positions Available Include

• Information security
• Management consulting data scientist
• Senior data scientist
• Customer data scientist

Average Data Scientist Salary at PwC 

The estimated total pay for a data scientist at PwC is $117,624 per year.

Notable Benefits

• Sick time that doesn’t count against PTO.
• Health care on-site.
• Stock options.
• Charitable gift matching.
• Fertility assistance.
• Sabbatical.
• Volunteer time off.
• Apprenticeship program.

4. Varsity Tutors

Varsity Tutors is a leading curated platform for live online learning benefiting both learners and experts.

Why Varsity Tutors Is Investing in Data Science

Thousands of students use Varsity Tutors for online Data Science instructors. Varsity Tutors’ mission is to transform the way people learn by leveraging artificial intelligence (AI), advanced technology, and the latest in learning science to personalize the learning experience. 

Positions Available Include 

• Data science expert (remote and various locations)
• GRE quantitative instructor
• JavaScript instructor

Average Data Scientist Salary at Company

According to Glassdoor, the estimated total pay for a data scientist at Varsity Tutors is $142,329 per year.

Notable Benefits

• 52 hours a year of one-on-one tutoring and free classes.
• Access to a health savings account (HSA).
• Ability to work remotely.
• Employee assistance program.
• Maternity and parental leave.

5. KPMG Accounting and Professional Services

KPMG is a team of dedicated problem solvers working in professional firms offering tax and audit services. The group is diverse and composed of dedicated problem solvers connected by a common cause, which includes turning insight into an opportunity for clients and communities in over 150 countries.

Why KPMG Is Investing in Data Science

KPMG applies data science to solve real-world business problems and operationalize AI. 

Positions Available

• Data scientist
• Data scientist, decision analysis (DA) and depreciation, depletion, and amortization (D&A)
• Manager, user experience (UX) data analytics insights designer

Average Data Scientist Salary at KPMG

The estimated total pay for a data scientist at KPMG is $115,835 per year.

Notable Benefits

• Mental health care.
• Performance bonus.
• Charitable gift matching.
• Childcare.
• Fertility assistance.
• Remote work.
• Commuter checks and assistance.
• Gym membership.
• Tuition assistance.

6. Amazon and AWS

Amazon, along with its subsidiary cloud computing company AWS, is one of the most widely recognized companies in the world for e-commerce, supply chain management, cloud, and AI and machine learning development.

Why Amazon Is Investing in Data Science

Amazon works to understand customers’ needs before they search for products. In addition, Amazon focuses on creating careers in areas that are sure to grow in years to come, including healthcare, machine learning, manufacturing, robotics, computer science, and cloud computing.

Positions Available

• Data science leader
• Data science manager
• Data science product manager

Average Data Scientist Salary at Amazon

The estimated pay for a data scientist at Amazon is $188,196 per year.

Notable Benefits

• Climate pledge and sustainability efforts.
• Student programs and internships.
• Upskilling training programs.
• Military apprenticeship.
• Education payment program.

7. Info Way Solutions

Info Way Solutions is an IT service and consulting company focusing on big data solutions, digital transformations, and cybersecurity solutions.

Why Info Way Solutions is Investing in Data Science

Info Way Solutions recognizes the explosion of data from more sources than ever before. Big data analytics offer significant opportunities for intuitive data insights. Its end-to-end services, matched with industry-specific skills and processes, help make data more straightforward to access and understand, accelerate time to capability, and improve data-driven business outcomes.

Positions Available

Average Data Scientist Salary at Info Way Solutions

The estimated total pay for a data scientist at Info Way Solutions is $141,815 per year.

Notable Benefits

• Flexible hours.
• Health insurance.

8. Microsoft Technology 

Microsoft is a global technology leader in software, hardware, gaming, cloud, edge, and digital transformation.

Why Microsoft Is Investing in Data Science

Microsoft’s mission to train “data scientists to tackle problems that really matter” is an understatement in almost every way.

And it is the tagline on the Data Science for Social Good (DSSG) website. A three-month summer program in Chicago, DSSG brings blossoming data scientists from across the country to work on data mining, machine learning, big data, and data science projects.

The Fellows (there are 48 of them) work in small teams on problems whose solutions rely heavily on data. The problem spaces run from education to health to energy to urban infrastructure issues. And by partnering with local governments, nonprofits, and federal agencies, they directly assist policymakers in making critical decisions.

Positions Available

• Principal data scientist
• Data science manager
• Research intern
• Investigative data scientist

Average Data Scientist Salary at Microsoft

The estimated total pay for a data scientist at Microsoft is $185,869 per year.

Notable Benefits

• Neurodiversity hiring program and ability hiring.
• Tuition assistance.
• Online and in-person professional development classes.
• Wellness reimbursement plan.
• Donation and volunteer matching.

9. Capital One Finance and Banking

In a Capital One data scientist role, you’ll be part of a team that employs the most advanced computing and machine learning technologies.

Why Capital One Is Investing in Data Science

As a startup, Capital One upended the credit card industry. It did this using statistical modeling to personalize every credit card offer individually. Indeed, data is at the center of everything this now Fortune 200 company does.

Positions Available

• Senior data scientist, commercial bank
• Senior associate, data scientist (Python developer)
• Manager, data scientist, customer protection data science

Average Data Scientist Salary at Capital One

The estimated total pay for a data scientist at Capital One is $138,222 per year. 

Notable Benefits

• Yearly bonuses.
• Charitable gift matching.
• Equity incentive plan.
• Pension plan.
• Reduced or flexible hours.
• Adoption assistance.
• Dependent care.
• Fertility assistance.
• Unpaid extended leave.
• Volunteer time off.

10. Accenture

Accenture is a global professional services company with leading digital, cloud, and security capabilities. Working for Accenture will provide employees with the opportunity to learn and expand their skills in big data.

Why Accenture is Investing in Data Science

The company is migrating an on-premises data warehouse to a new data and analytics platform. It combines commercial innovation and leading-edge technologies to deliver an integrated, mobile, interactive experience far exceeding expectations. 

Positions Available

• Data platform specialist
• Epic radiant consultant
• Senior marketing data scientist

Average Data Scientist Salary at Accenture

The estimated total pay for a data scientist at Accenture is $119,634.

Notable Benefits

• Free annual flu shots.
• Legal services plan.
• Personal excess liability insurance.
• Identity theft insurance.
• Pet insurance.
• Gym membership discounts.
• An online mall provides discounts on various retail offerings.

Other Companies Hiring for Data Scientists

The following is a chart with additional companies seeking data scientists.

What Is the Average Salary of a Data Scientist?

While the average salary range of a data scientist varies per region, the role is well-paying, with the opportunity to increase earnings as you develop skills.

Let’s take a look at what a few different resources say about the average salary of a data scientist. The pay rates are based on data from 2022 and reference a year’s salary.

According to Glassdoor, the average salary of a data scientist is $88,342 a year. Glassdoor reports the high end of pay to be $143,000 a year, with a low end of $55,000 a year.

Salary.com has comparable wages, ranging from around $60,000–$86,000 a year for an entry-level data scientist. For roles requiring more experience, employees can expect to make anywhere from $240,000–$330,000 a year.

The U.S. Bureau of Labor Statistics lists data scientists’ salaries according to location. For example, if you’re a data scientist in California, you can expect an average wage of $133,000 a year. If you’re working in New Jersey, you can expect to earn around $120,000 a year.

What Should You Consider When Choosing a Company as a Data Scientist?

Choosing what company to work for can take time and effort. As a data scientist or someone looking to break into the field, choosing a company can seem daunting, but it becomes easier with a bit of help.

As with any new role, it’s best to think about what kind of company you want to work for and then go from there. Here are some pointers to get you started:

• Consider getting an education. Companies hiring data scientists want to hire data scientists with certifications under their belt.
• Pick more than one industry to work in. For example, widen your reach by going after tech and finance roles rather than just finance roles.
• Consider what type of company you want to work for. Aside from industry, think about what kind of company you’d like to work for based on employee size and other factors.
• Make a list that details your top 5–10 companies. A list will help you prioritize your needs as well as keep your job search organized.
• Do your research on each company. Go beyond the surface level. If you don’t know anything about the company, it’s likely to become apparent in an interview.
• Be sure to see if their values align with yours. It’s not fun working a job where no one else cares about the values you have.
• Check out their benefits packages. Do they have what you need? It’s also nice to check out benefits that go beyond medical and dental, like student loan repayment help.
• Learn about their upper management. This goes hand-in-hand with researching the company. You’re more likely to get hired if you know your stuff.
• Tailor your résumé to each company. Be sure to have a cover letter and references ready.
• Practice for interviews. Practice answering questions with a friend or in front of a mirror.
• Determine if the company is the right fit. After your first or second interview, you’ll better understand how the company works. Remember, an interview is just as much for you as it is for them.
• Remember that job hunting takes time, so be persistent. Don’t get discouraged after a rejection. Remember that each “no” is one step closer to a “yes.” Stay positive.

How We Selected the Top Companies Hiring Data Scientists 

While researching the top companies hiring data scientists, we want to include those companies that are not only hiring data scientists but are known as the best companies to work for in any industry.

The companies listed are included and ranked based on the number of job openings available on LinkedIn as of January 2023. The companies featured have the most current openings and tend to have employees numbering in the thousands. These are the companies that are sought after by many data scientists already in the field as well as those wanting to make a name for themselves.

Please note that the open positions listed are just a sampling of positions the job has available and that not every benefit a company offers is listed.

Working at the Best Companies for Data Scientists 

Working as a data scientist will help net you a role in various industries. Whether you’re after a job in finance, healthcare, manufacturing, or tech, you’re sure to find an opportunity at one of the above companies to fit your goals. While today’s job market may look bleak, as many companies are laying off their talent, the need for a data scientist will not disappear soon.

In 2020, Gartner established the NDR solution category, renaming the previously called “network traffic analysis.” This move helped to evolve the growing importance of network detection response capabilities. NDR machine learning, heuristic analysis, and non-signature-based analytical tools and techniques enable teams to respond to threats and anomalous traffic that other tools may miss. To help protect a user’s network and devices, an organization needs to subdue attacks from multiple angles, which is where an NDR comes in:

1. ExtraHop Reveal(x)

The mission of Seattle-based ExtraHop is to help organizations stop advanced threats with uncompromised security. 

Reveal(x) key features

• Operates with complete visibility, real-time detection, and intelligent response
• Detects what’s happening in an organization’s cloud environment 
• Threat detection with full context across a hybrid enterprise
• Artificial intelligence (AI)-based detection
• Automated detection, investigation, and response via integration with third-party security tools, such as CrowdStrike and Phantom
• Automated inventory for discovering and classifying network devices
• Peer group detection to sort devices into behavioral groups

User review

“Although I saw the console for the first time, I placed it in the top 10 because the team had put so much thought into the UI as well, and the user experience was awesome since the first day! I’m always impressed by the search features and capabilities; you may utilize the search function to narrow down your analysis down to asset levels of any kind,” says a user at Gartner Peer Reviews.

Honors

Won the 2022 Cyber Security Excellence award

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2. Cisco Secure Network Analytics

San Jose, California-based Cisco is leader in the networking market. 

Cisco Secure Network Analytics key features

• Detects and responds to threats
• Uses machine learning and behavioral modeling
• Cloud-native visibility across major cloud providers, like Amazon Web Services, Microsoft Azure, and Google Cloud
• Visibility across entire network infrastructure with a single solution
• Scans network traffic
• Behavior analysis for detection
• Distributed denial-of-service (DDoS) identification
• Telemetry lets a security team know who is on the network and what they’re doing

User review

“[Cisco Secure Network Analytics] provides detailed information on host incoming as well as outgoing traffic, which helps us to understand exact bandwidth requirement or to prevent any unethical activities going on in organization network,” says a user at TrustRadius.

Honors

Cisco won the SC Media Award for Best Security Company.

Trial

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3. Darktrace/Network

Based in Cambridge, U.K., Darktrace also has offices in Singapore, San Francisco, and the Netherlands. 

Darktrace/Network key features

• Self-learning AI to learn what’s typical for an organization
• Neutralizes both known and unknown threats
• Insider threat detection
• A version for industrial systems
• Automatic responses
• Easy-to-understand reports

“Darktrace’s IES provides us with a level of confidence that we would otherwise miss in an ever-evolving threat landscape,” says a user at Gartner Peer Insights.

Honors

The company has won the AI Cyber Product of the Year for the last four years the U.K.’s National Cyber Awards.

Demo

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4. Vectra Platform

Based in San Jose, California, Vectra helps organizations detect, prioritize, investigate, and respond to cyberthreats within seconds of getting attacked.

Vectra Platform key features

• AI-based detection
• Supports hybrid environments
• Playbooks for responses

User review

“The support behind this product is top-notch; they will consistently reach out to make sure functionality is being maintained and if there are any technical hiccups or tuning questions that they would be happy to assist with,” says a user at Gartner Peer Insights.

Honors

Vectra brought home several awards from the SC Awards Europe in 2022, including for Best Behavioral Analytics/Threat Detection.

Demo

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5. Gigamon ThreatINSIGHT

Gigamon is based in Santa Clara, California and offers solutions to some of the top challenges facing online businesses, such as having network detection tools in several locations without whole-enterprise visibility and payment card industry (PCI) compliance requiring all external traffic using TLS version 1.1 or higher.

ThreatINSIGHT key features

• Detect, hunt, and investigate threats using one cloud-based security solution
• Software-as-a-service (SaaS) package
• Secure Sockets Layer (SSL) offloading
• Works with Cisco devices
• Offers use cases for operational tasks, like decommissioning servers or diagnosing switch misconfigurations
• Focus on high-quality detections helps prevent false positives

User review

“Once set up and configured, the implementation is very robust. We have equipment that has been running for years without the need to reboot,” says a user at Gartner Peer Insights.

Honors

Gigamon has won several awards in its space, including being awarded the Silver Globe in the Golden Bridge Business and Innovation Awards.

Demo

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6. CrowdStrike Falcon Firewall Management

CrowdStrike, based in Austin, Texas, offers straightforward firewall management with reduced complexity.

Falcon Firewall Management key features

• Easily create, enforce, and maintain firewall rules and policies across Windows and macOS environments
• Build new policies based on templates
• Create a firewall rules group once and reuse it in multiple policies
• Quickly propagate changes to the appropriate policies
• Focus on high-quality detections helps prevent false positives

User reviews

4.8 out of 5 overall by reviewers at Gartner Peer Insights.

“CrowdStrike is the market leader in next-generation endpoints security provided via the cloud,” says a user at Gartner Peer Insights.

Honors

CrowdStrike has been recognized for several years by Gartner as a Customers’ Choice for endpoint protection platforms, including 2021. 

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7. Cynamics

Boston-based Cynamics knows that the real problem around the increasingly popular network-based attacks is that these attacks are widespread and costly. The global cost of cybercrime is estimated to reach $10.5 trillion by 2025, according to Cynamics.

Cynamics key features

• Complete network visibility
• Easily integrated with any network size or type
• Uncovers hidden threat patterns in real-time, deploying patented AI technology
• Requires no agents, sensors, or probes for scalability
• Self-managed autonomous technology

User review

“I saw many products, but when I came across Cynamics and saw that they claim to combine AI and deep learning to autonomously detect and analyze patterns using 1% of the traffic and gain 100% visibility, I said this is [too] good to be true. On top of that, no agents. I said I need to give them a shot. Long story short, their claim was on point,” says a user at Gartner Peer Reviews.

Honors

Named TAG Cyber’s Distinguished Vendor in 2022.

Trial

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An NDR can help security teams detect, identify, and respond to malware and attempted attacks on user networks and devices. These devices, whether on the premises, on the cloud, or in hybrid environments, will all benefit from an NDR in place. See below to learn all about why NDR is a critical part of a network security strategy: 

Why do companies use NDR solutions?

• What are the benefits of network detection and response?
• Why is network detection and response important?
• What cyberthreats does network detection and response defend against?
• Bottom line

What are the benefits of network detection and response?

Streamline security response

NDR expands on real-time monitoring and analysis while solutions integrate security, automation, and response technology to streamline and automate response options.

Save time

NDR solutions gather data across environments and use machine analytics to expose threats quickly. They then provide incident response and threat-hunting efforts that security teams don’t have to do themselves. 

Save money

A team can save money with an NDR that provides real-time network insights and analytics and gathers data from within a work environment to add relevant, contextual information and make breach investigations more efficient and less costly projects.

Why is network detection and response important?

Increase of security incidents

The number of security incidents has increased over the last few years. These staggering increases in attacks have created the need for better, faster security software. And not just for large companies. While most attackers focus on big corporations with large pockets, small and medium-sized businesses (SMBs) are targeted 43% of the time. This is because attackers have found it far easier to attack smaller businesses with less robust cybersecurity systems in place. They then use the stolen data and access to gain access to larger partner enterprises and even customers. Unfortunately, an organization of any size is vulnerable to an attack. 

Detecting threats isn’t enough

These increasingly-popular attacks wreak havoc on their victim companies. In addition, we know network-based attacks have become increasingly popular for scammers, often causing significant impacts on the victim companies. Unfortunately, other security tools may miss these advanced, more robust attacks, and may require interference and help from security and IT teams. NDR solutions move beyond signature-based detection by implementing machine learning and data analytics to analyze network traffic, responding to threats in real time. 

Need for rapid response

NDR tools use machine learning and behavioral analytics to monitor network traffic and develop a baseline of activity. Once they understand the baseline behaviors, an NDR can determine when new and different traffic occurs and what needs immediate investigation and response. That means when something fishy is detected on a company’s network, an NDR can recognize it, analyze it, and respond in seconds. 

Use of forensic analysis 

Using a process of detecting intrusion patterns, focusing on attacker activity, an NDR can determine how threats breach and move through a network. 

They analyze network traffic data collected from different sites and network equipment, such as firewalls. In addition, NDRs monitor anomalous network traffic to detect attacks and determine the nature of attackers.

What cyberthreats does network detection and response defend against?

NDR tools have many functions that make them ideal for any organization’s day-to-day network security. An NDR can help defend against many attacks and threats that networks and security teams face today. 

Suspicious network traffic that traditional tools miss 

Not to be confused with EDR, which focuses on monitoring and preventing endpoint attacks, NDRs focus on monitoring communications and creating real-time network visibility. They also provide timely alerts for incident response teams. In addition, an NDR can detect patterns and anomalies in all network traffic, thereby stopping and eliminating suspicious or malicious traffic. 

In addition, an NDR differs from traditional cyber detection tools like EDR in that it doesn’t utilize a specialist to understand malignant activity. Instead, it depends on an organization to investigate traffic across on-premises and remote-based jobs. By using non-signature-based detection techniques, NDR security arrangements tend to stop threat attacks in the works before they can bring any damage. 

Scanning for traffic that doesn’t adhere to trusted or recognized safe browsing behavior, NDR systems persistently monitor and analyze basic enterprise network information to establish a baseline of typical network activity. Whenever suspicious network traffic designs diverge from this baseline, NDR tools caution security experts that risks might be taking place on their network. 

Non-malware threats

Non-malware threats, including insider attacks and credential abuse, are those in which the attacker doesn’t need to install anything on a network or machine. A simple click on a link can cause an employee to infect an organization’s network unknowingly. An NDR can detect these threats, which are hidden behind seemingly normal behavior. These attacks have no identifiable code or signature that makes other software see them. They also do not tend to have a particular behavior making it necessary for an organization to have software beyond traditional, heuristic scanners. An NDR now becomes invaluable as a way to recognize this type of breach and immediately respond. 

Suspicious accounts and IP addresses

NDR solutions help heighten and automate security workflows. For example, a team can automate routine responses to meet specific needs and to stop specific threats. Automating network security allows businesses to focus on other vital needs. A great example of an NDR working for security is one automatically disabling an account or blocking an IP address in response to an attack without the need for a team to intervene, which brings us to our last point. 

Bottom line

A network and detection response system is vital for any small or large-scale company that uses a network. Any company with employees working on a computer, either in-office or at home, is susceptible to attacks. An NDR can help teams detect many of these threats and determine the best course of action or response for a security team to take. Many of these actions are done immediately, without human interference, cutting down response time while helping eliminate the risk of data breaches. Using techniques such as behavioral analytics, machine learning, and artificial intelligence, an NDR can help bring an organization up to speed when it comes to network security.