15 Best Companies to Work for As a Data Scientist in 2024

In 2024, the data science gold rush is in full swing. Companies seek talented data scientists to unearth the hidden insights within their ever-growing data mountain. So, if you're looking for the best companies to work for as a data scientist, look no further!

In this comprehensive blog, we'll explore the best companies in data science that offer unparalleled benefits and opportunities to their employees.

Whether you seek competitive salaries, futuristic projects, or a diverse work culture, we've got you covered. Enable your data science skills and embark on an exciting career journey with one of these companies.

Let's look into the topics we will be covering in this blog -

• 15 Best Companies to Work for as a Data Scientist in 2024

• Salary Insights – How much do data scientists make in different companies?

• Tips Before Applying for a Data Scientist Job

• Factors to consider before applying for a Data Scientist job

• How To Find Data Science Jobs

• FAQs about Data Science Companies

15 Best Companies to Work for As a Data Scientist in 2024

1. Google (Alphabet)

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Google, the renowned tech giant, is known for its innovation and state-of-the-art technologies. With a strong focus on machine learning and artificial intelligence, Google offers an engaging environment for data scientists to pioneer complex algorithms.

At Google, data scientists thrive in a culture that fosters exploration, collaboration, and pushing the boundaries of innovation. Moreover, flexible work options, generous compensation packages, and access to cutting-edge resources further elevate Google as a dream workplace for data scientists.

Career Page: Work at Google

2. Facebook (Meta)

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Facebook, also known as Meta, is a global social media behemoth with billions of users worldwide. Facebook is renowned for its user-friendly technologies and innovative spirit. With a strong emphasis on research and development, Facebook offers a dynamic environment for data scientists seeking to make a significant impact on a global scale.

Career Page: Work at Facebook

3. Microsoft

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Microsoft stands out as a global leader in software development and cloud computing. Renowned for its unwavering commitment to advancing data science, Microsoft provides an enriching environment for professionals in this field.

Data scientists at Microsoft have the opportunity to work on diverse projects spanning various domains. Microsoft also offers competitive compensation, flexible work arrangements, and state-of-the-art technologies.

Career Page: Work at Microsoft

4. Amazon

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Amazon is another sought-after destination for data scientists. With its wide array of services, from e-commerce to cloud computing, Amazon provides an exciting and dynamic environment for data science professionals.

At Amazon, data scientists are part of a culture that values innovation and problem-solving. They have access to cutting-edge tools and technologies, including Amazon Web Services (AWS), which allows them to tackle complex challenges and drive impactful solutions.

Career Page: Work at Amazon

5. IBM

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IBM, a pioneer in technology and consulting, is a prime destination for data scientists seeking innovative opportunities. IBM has a rich history of technological advancements and a strong emphasis on data-driven solutions.

One of the key benefits of joining IBM as a data scientist is the opportunity to work across diverse industries and domains. Whether in healthcare, finance, or cybersecurity, IBM offers many projects that allow data scientists to apply their skills and expertise to solve real-world problems.

Career Page: Work at IBM

6. NVidia

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Nvidia is the pioneer in developing graphics processing units (GPUs) and is a dream destination for data scientists. NVidia's main focus areas are GPU-accelerated computing and artificial intelligence (AI). At Nvidia, data scientists have access to powerful hardware and software solutions designed to accelerate large-scale data processing.

The best thing about working at Nvidia is the opportunity to contribute to groundbreaking research and development projects, from advancing AI and machine learning algorithms to optimizing performance in areas like autonomous vehicles and healthcare analytics.

Career Page: Work at NVidia

7. VMware by Broadcom

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VMware is a global leader in cloud infrastructure and digital workspace technology. They offer an intriguing platform for data scientists. VMware's primary focus is on virtualization and cloud computing.

At VMware, data scientists can work with vast amounts of data generated by virtualized environments, cloud deployments, and software-defined data centers. One key attraction of working at VMware as a data scientist is the chance to collaborate with top-tier engineers, developers, and researchers in cloud computing.

Career Page: Work at VMware

8. Oracle

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Oracle is the global leader in enterprise software and cloud solutions. With its extensive suite of products and services spanning databases, analytics, and AI, Oracle provides a rich ecosystem for data scientists.

At Oracle, data scientists have access to a wealth of data from diverse sources, including Oracle's cloud platforms, enterprise applications, and customer databases. Moreover, Oracle offers competitive compensation packages, comprehensive benefits, and a supportive work culture that values innovation and continuous learning.

Career Page: Work at Oracle

9. PwC

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PwC (PricewaterhouseCoopers) is one of the world's largest professional services firms and one of the Big Four accounting firms. They provide a compelling environment for data scientists with a strong focus on providing audit, consulting, and advisory services. PwC leverages data science to deliver innovative solutions to its clients across various industries.

Career Page: Work at PWC

10. JPMorgan Chase & Co.

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JP Morgan Chase is one of the largest financial institutions in the world. It offers a dynamic environment for data scientists and focuses on innovation and technology-driven solutions. JP Morgan Chase uses data science to drive insights, enhance decision-making, and deliver value to its clients.

Data scientists can access vast amounts of financial data, market trends, and customer insights, presenting exciting opportunities to develop advanced analytics models and predictive algorithms.

Career Page: Work at JPMorgan Chase & Co.

5 Up and Coming Companies for Data Scientists

1. Splunk

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Splunk is a leading software platform for analyzing and visualizing machine-generated data. It allows organizations to collect and index data from various sources, including servers, applications, and devices, and then analyze this data to gain valuable insights. For data scientists, Splunk offers a powerful platform for working with large volumes of data and performing advanced analytics tasks.

Career Page: Work at Splunk

2. Cloudera

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Cloudera is a leading provider of enterprise data management and analytics solutions. Cloudera is like a toolbox for handling big data. It helps organizations store, organize, and analyze all this data efficiently.

One of Cloudera's best parts is that it supports different tools and programming languages that data scientists use, like Python and R. This means data scientists can work with Cloudera using the tools they're already familiar with.

Career Page: Work at Cloudera

3. Databricks

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Databricks is a new company that originated in academia and the open-source community. Databricks is an analytics platform designed to simplify the process of building big data and artificial intelligence (AI) solutions.

For data scientists, Databricks offers a powerful platform for developing and deploying machine learning models at scale. It provides interactive notebooks like digital workspaces where data scientists can write and execute code, visualize data, and share insights with their team.

Career Page: Work at Databricks

4. Numerator

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Numerator is a market intelligence company specializing in providing businesses with data and insights. It collects and analyzes data from various sources, including retail transactions, online purchases, and consumer surveys, to provide clients with valuable insights into market trends and consumer behavior.

Data scientists at Numerator may be involved in developing predictive models, conducting statistical analysis, and building data-driven solutions to solve complex business problems.

Career Page: Work at Numerator

5. Teradata

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Teradata is a leading provider of data warehousing and analytics solutions for enterprises. The company offers a range of products and services that help organizations manage and analyze large volumes of data.

Teradata offers a collaborative and dynamic work environment where data scientists can collaborate with cross-functional teams of analysts, engineers, and business stakeholders.

Career Page: Work at Teradata

Salary Insights – How much do data scientists make in different companies?

According to recent data, the average salary of a data scientist in the US is around $124,106.

• Entry-level data scientists: $80,000 to $120,000 per year

• Experienced data scientists: $120,000 to $160,000 per year

Company wise average salary:

1. Google:

Average Monthly Salary: $10,467

Average Yearly Salary: $147,830

2. Facebook (Meta):

Average Monthly Salary: $11,952

Average Yearly Salary: $168,813

3. Microsoft:

Average Monthly Salary: $9,959

Average Yearly Salary: $140,656

4. Amazon:

Average Monthly Salary: $10,387

Average Yearly Salary: $146,699

5. IBM:

Average Monthly Salary: $9,228

Average Yearly Salary: $130,332

6. NVidia:

Average Monthly Salary: $12,411

Average Yearly Salary: $175,286

7. VMware by Broadcom:

Average Monthly Salary: $9,653

Average Yearly Salary: $136,332

8. Oracle:

Average Monthly Salary: $8,153

Average Yearly Salary: $115,158

9. PwC:

Average Monthly Salary: $8,192

Average Yearly Salary: $115,697

10. JPMorgan Chase & Co:

Average Monthly Salary: $8,433

Average Yearly Salary: $119,106

11. Splunk:

Average Monthly Salary: $9,394

Average Yearly Salary: $112,728

12. Cloudera:

Average Monthly Salary: $10,230

Average Yearly Salary: $144,489

13. Databricks:

Average Monthly Salary: $8,953

Average Yearly Salary: $126,448

14. Numerator:

Average Monthly Salary: $7,047

Average Yearly Salary: $99,532

15. Teradata:

Average Monthly Salary: $8,698

Average Yearly Salary: $122,843

Tips Before Applying for a Data Scientist Job

1. Research about the company: Understand the company's mission, vision, projects, and work culture to tailor your application. Ensure your qualifications match the job requirements.

2. Updated Skills: Stay updated with technical knowledge and enhance your skills in programming, statistics, and machine learning.

3. Prepare for the Interview:

• Review the basic concepts of data science.

• Practice coding exercises.

• Be ready to discuss your projects and problem-solving approaches.

4. Stay Updated with the Latest Trends: Stay updated with the latest tools, techniques, and technologies in data science.

5. Networking: Connect with other data science professionals, join related communities, and participate in competitions and projects to expand your network.

6. Customize your Resume: Tailor your resume, cover letter, and application to highlight relevant skills and experiences for the specific company and role.

Factors to consider before applying for a Data Scientist job

• Understand the Job Responsibilities and Role: Review the job description carefully to understand the responsibilities and expectations associated with the role. Ensure the job aligns with your skills, interests, and career aspirations.

• Technical Skills and Expertise: Test your proficiency in key technical areas such as programming languages, machine learning algorithms, statistical analysis, and data visualization.

• Knowledge of Industry and Domain: Data science roles span various sectors, including technology, finance, healthcare, e-commerce, and more. Ensure whether you have the proper domain knowledge of the specific industry or not.

• Company Culture and Values: Research about the company's culture, values, and work environment to determine if they align with your preferences and professional goals.

• Opportunities for Learning and Growth: Assess the company's commitment to employee development and ongoing learning. Look for opportunities for skill development, training programs, and career advancement within the organization.

• Compensation and Benefits Package: Evaluate the salary, benefits, and rewards offered by the company, such as health insurance, retirement plans, and stock options.

• Company Reputation in the Market: Research the company's reputation, financial stability, and track record. Consider factors such as industry recognition, customer satisfaction, and employee reviews.

How To Find Data Science Jobs

• Online Job Boards and Websites: Check out popular job search platforms such as LinkedIn, Indeed, Glassdoor, and Monster to find data science job openings. Use relevant keywords such as "data scientist," "machine learning engineer," or "data analyst ."

• Career Pages: Search the career pages of companies you are interested in working for. Many companies post job openings directly on their websites.

• Professional Networking: Use social media platforms to network with professionals in the data science community. Building relationships and expanding your network can lead to valuable job opportunities and referrals.

• Recruitment Agencies: Consider contacting recruitment agencies that specialize in data science and analytics jobs. These agencies can help you with relevant job opportunities and assist with resume writing and interview preparation.

• Online Learning Platforms: Many online learning platforms, such as Coursera, Udacity, and Kaggle, offer job boards and career resources tailored to data science professionals.

• Events and Meetups: Attend local or virtual data science meetups, workshops, and conferences to network with industry professionals and discover job opportunities.

• Social Media Platforms: Follow data science-related hashtags, groups, and social media influencers to stay informed about job openings and industry news.

• Alumni Networks and University Career Services: Enquire about job openings in your alumni network and university career services. Many universities host job fairs, networking events, and workshops tailored to data science students and alumni.

• Freelancing and Consulting Opportunities: Explore freelance platforms like Upwork, Freelancer, and Fiverr to find short-term data science projects and opportunities.

FAQs about Data Science Companies

1. What kind of projects do data scientists work on?

The answer depends on the type of company and industry. Some common project areas include:

• Machine learning and AI development

• Big data analytics and processing

• Risk management and fraud detection

• Personalized experiences and user behavior analysis

• Medical research and diagnostics

2. What are the work cultures like at data science companies?

Many data science companies are known for their fast-paced and dynamic environments. They emphasize on technical expertise, innovation, and team-oriented cultures.

3. What skills and qualifications are data science companies looking for?

Companies typically look for candidates with a strong foundation in:

• Statistics and machine learning

• Programming languages like Python and SQL

• Data visualization

• Problem-solving and critical thinking

• Communication and collaboration skills

4. What red flags should you look for when applying for a data science job?

• Lack of clarity in the job description: If the job description is vague or unclear about the responsibilities and expectations, it may be a sign that the company doesn't understand what they're looking for.

• Unrealistic expectations: If the job requirements seem overly demanding or unrealistic, such as requiring expertise in a wide range of technologies or tools, it may indicate that the company has unrealistic expectations for the role.

• Limited growth opportunities: If there are few opportunities for career growth within the company, it may indicate that the company doesn't value its employees' long-term career development.

• Lack of transparency in the hiring process: If the hiring process is opaque or lacks transparency, such as not providing feedback after interviews or not communicating clearly about the next steps, it may be a sign of poor communication issues within the company.

5. Are data scientists paid well?

Yes. According to recent data, the average salary of a data scientist in the US is around $124,106. This number will likely increase as the demand for skilled data scientists will grow in the coming years.

6. Is Data Science a Good Career?

Yes, the demand for data scientists is increasing day by day. Almost every industry and field requires the services of data scientists.

Conclusion

In the rapidly evolving field of data science, choosing the right company is crucial for your career growth. From industry giants like Google and Facebook to up-and-coming innovators such as Splunk and Cloudera, opportunities abound for data scientists seeking to make their mark in 2024 and beyond.

As the demand for skilled data scientists grows and the importance of data-driven decision-making becomes increasingly apparent, the future is bright for those pursuing a career in this dynamic field. So, seize the opportunity, explore your options, and chart your course toward success in the exciting world of data science.