Top 25 Data Science Companies in India - Career in Data Science

From online shopping to food delivery, everything produces data—yet its true value comes when we make sense of it. That’s where the role of data scientists, engineers, and analysts becomes important. They help businesses predict, personalize, and make smarter decisions.

In India, data science has become one of the most exciting career paths. The government is fueling it with the IndiaAI Mission, while global companies have built 1,700+ capability centers here. Add India’s own analytics firms, and opportunities are everywhere.

The real question is: which companies are the best to build your career with? In this article, we’ll cover the Top 25 Data Science Companies in India, plus what roles are hot, what skills matter, and how to grow in this fast-moving field.

India’s AI & Data Boom: What’s Fueling It

India is in the middle of a once-in-a-generation AI and data shift. Two tailwinds matter:

1. Serious national investment. In March 2024 the Government of India approved the IndiaAI Mission with a ₹10,300+ crore (~US$1.25B) outlay to build compute, datasets, skills, startups, and responsible AI guardrails. That’s not just PR; it’s Cabinet-approved policy. (Press Information Bureau, Reuters)
2. GCCs are booming. Multinationals now build end-to-end products from India via Global Capability Centers (GCCs). India hosts ~1,700–1,900 GCCs today and the market is projected to touch ~US$100B by 2030. Translation: there’s real, compounding demand for data folks across BFSI, retail, healthcare, manufacturing, media, and tech. (Reuters, The Times of India)

If you’re entering or upskilling in data, this is a good decade to do it.

What roles are in demand (and why they’re everywhere)

• Data Analyst / BI Analyst – turns messy business data into clean dashboards and decisions.
• Data Scientist – builds models: classification, forecasting, recommendations, uplift.
• Machine Learning Engineer / MLOps – makes those models scale in production.
• Data Engineer – pipelines, warehouses, lakehouses, real-time streaming.
• Analytics Translator / Decision Scientist – bridges business questions and model design.
• GenAI Roles – prompt engineering, retrieval-augmented generation, evaluation, and guardrailing.

GCCs and Indian tech services are hiring these because companies aren’t just “experimenting” anymore; they need production AI/analytics to drive revenue and save costs. NASSCOM/Zinnov peg the GCC market growth to ~US$99–105B by 2030—fuel for sustained hiring. (Reuters)

Read Also: Data Science Certification Course

How salaries look right now

Comp varies by city, domain, and company tier, but a reliable market pulse:

• Data Scientist in India: widely reported ranges sit roughly from ₹4–7 LPA for entry roles, mid-career often in the ₹15–25 LPA band, and senior/principal roles well above that depending on company and equity. Cross-check typical ranges on AmbitionBox when you’re comparing offers. (AmbitionBox)
• The big picture: Pay keeps rising with hands-on deployment experience (MLOps), cloud fluency, and domain depth (BFSI, retail, healthcare). The IndiaAI Mission’s skills focus should also keep the pipeline and wages healthy over the next few years. (Press Information Bureau)

Tip: When comparing offers, look at total compensation (bonus, ESOPs/RSUs, learning budget) and the kind of projects you’ll ship in your first six months.

Read Also: Data Science vs. Cyber Security: Which Career is Best for You?

The Top 25 Data Science Companies in India (in 2025)

Below is a pragmatic list you can use for targeting applications. It blends:

• Indian analytics leaders,
• global GCCs with serious data orgs in India, and
• large services firms scaling Data & AI.

Importantly, all 25 below featured in Analytics India Magazine’s 2024 “50 Best Firms for Data Scientists to Work For”—a survey focused on actual employee-centric practices (upskilling, flexibility, DEI, recognition). Take that as a quality signal while you do your own due diligence. 

1. Intuit (GCC)

Known for financial products like QuickBooks and TurboTax, Intuit’s India GCC focuses on fintech innovation. Data professionals here work on causal inference, recommendation systems, and personalization at scale. Great place if you want to see how experiments directly impact millions of small businesses worldwide. Team members build algorithms and prototypes using financial data from over 100 million customers and small businesses. This offers you a front-row seat to impactful experimentation and AI-driven product development.

2. American Express (GCC)

Amex has long been a pioneer in risk analytics and fraud detection. Its Indian teams are recognized for model governance, fairness, and explainability—critical for financial services. A top choice if you’re interested in credit scoring, fraud prevention, and advanced marketing analytics. In India, Amex teams also work on personalized offers, loyalty programs, and customer lifetime value models—making it a strong place for data scientists who want to see analytics tied directly to customer engagement.

3. Walmart (GCC)

Walmart Global Tech India builds AI systems that power search, recommendations, and supply chain optimization. Think billions of transactions and real-time decision-making. Excellent exposure for anyone keen on retail data science at planetary scale. The team also builds models for last-mile delivery, dynamic pricing, and real-time inventory planning—perfect exposure to how AI fuels global retail at massive scale.

4. Lowe’s (GCC)

At Lowe’s India, data science supports retail operations, personalization, and inventory management. It’s a great setting to see how predictive analytics improves customer experience and store efficiency across thousands of locations. Data professionals here also contribute to supply chain planning and store layout optimization, linking analytics to both digital and in-store customer experiences.

5. Genpact

One of the largest data-driven services firms, Genpact applies AI to finance, supply chain, and manufacturing. Known for its process-driven culture, it’s an ideal place to learn how data science transforms traditional enterprises at scale. Its analytics teams often work on large-scale transformation projects, offering exposure to cross-industry consulting and practical applications of AI in business workflows.

6. EXL

Strongly positioned in insurance and healthcare analytics, EXL is a leader in decision sciences. Employees get exposure to actuarial data, claims prediction, and customer analytics in highly regulated industries. The company also invests heavily in automation and digital transformation, giving data scientists a chance to combine domain expertise with advanced AI in regulated industries like insurance and healthcare.

7. Tiger Analytics

Born in India and now global, Tiger delivers end-to-end ML solutions across industries. Known for its startup-like energy, Tiger gives data scientists ownership of full lifecycle projects, making it great for rapid learning. Teams work across sectors from retail and BFSI to industrial IoT, making it an ideal choice for those who want variety, global client exposure, and the pace of a high-growth analytics firm.

8. Fractal

A pioneer in decision sciences, Fractal also incubates AI products like Qure.ai (healthcare imaging) and Cuddle.ai (AI assistant). With Fortune 500 clients in CPG, retail, and financial services, Fractal offers opportunities to work on both consulting projects and proprietary AI product development. The firm is respected for its culture of innovation and R&D-heavy projects.

9. Tredence

Branded as the “last-mile analytics” company, Tredence ensures models drive measurable business outcomes. With strong retail, telecom, and CPG clients, employees here gain hands-on MLOps exposure and production deployments. It also emphasizes data storytelling and business integration, ensuring that analytics teams see their models influence real decisions in marketing, supply chain, and customer engagement.

10. AB InBev (GCC)

As the world’s largest brewer, AB InBev’s GCC uses data to optimize demand forecasting, route-to-market, and pricing strategies. An excellent place to see analytics applied in fast-moving consumer goods (FMCG) at global scale. Its India GCC also develops analytics for sustainability initiatives, logistics efficiency, and smart manufacturing—great exposure to applying AI in a consumer brand with global reach.

11. Chubb (GCC)

Chubb, the global insurer, uses its India hub for P&C insurance modeling and claims analytics. Great exposure if you want to understand risk models, policy pricing, and claims fraud detection. The India teams also explore catastrophe modeling, reinsurance analytics, and digital claims automation—ideal if you want to apply AI in core insurance operations.

12. Rakuten (GCC)

Rakuten India is a hub for e-commerce, ads, and fintech analytics. With work on multilingual search and recommendations, it’s a strong choice for those interested in applied machine learning for consumer internet. You’ll also find projects in payments, ad-tech optimization, and personalized shopping journeys, making it a rich environment for those who like real-world ML at internet scale.

13. Aays Analytics

A niche analytics firm growing quickly, Aays offers hands-on projects and direct client exposure. Its smaller size means faster learning cycles, closer client interaction, and opportunities to work across both technical and business problem-solving. Perfect for those who want smaller teams and accelerated responsibility in their early career.

14. TheMathCompany (MathCo)

A consulting powerhouse, MathCo builds AI accelerators and reusable frameworks for clients. If you want to work across domains and projects rapidly, MathCo offers a variety-rich environment. Teams here often work with Fortune 500 firms, giving you exposure to global-scale data problems while leveraging MathCo’s accelerators for speed and efficiency.

15. Société Générale (GCC)

The French banking giant runs advanced risk, compliance, and trading analytics from its India hub. Great fit for data scientists who enjoy the intersection of finance, regulation, and high-performance modeling. It’s also a hub for quantitative finance, algorithmic trading support, and anti-money laundering analytics—great exposure to high-stakes, real-time decisioning.

16. Wipro

Wipro is a leader in enterprise-scale data platforms and AI programs. As a service giant, it gives exposure to multi-industry, global transformation projects involving cloud and big data modernization. Teams at Wipro also build large-scale industry cloud solutions and enterprise data lakes, giving professionals a chance to work at the intersection of big data engineering and applied AI.

17. EY (GDS/GCC)

EY’s India hub focuses on risk analytics, finance transformation, and responsible AI. Employees gain insight into trustworthy AI practices, a skill increasingly valued in regulated industries. From fraud detection to ESG analytics, EY provides opportunities to work on high-impact use cases where governance and transparency matter as much as accuracy.

18. Landmark Group (GCC)

Known for its retail and loyalty programs, Landmark GCC applies data science to customer segmentation, personalization, and store operations. Great place to work if you’re drawn to consumer behavior and retail analytics. The GCC also manages one of the region’s biggest loyalty ecosystems, letting data scientists see how analytics drives repeat sales and customer retention at scale.

19. Tech Mahindra

Tech Mahindra utilizes data and AI in telecom and manufacturing, two sectors with massive datasets. Its projects increasingly include GenAI solutions, making it an evolving space for innovation. Tech Mahindra is also growing capabilities in digital twins, 5G analytics, and predictive maintenance—ideal for those who want to work on cutting-edge telecom and manufacturing data projects.

20. JCPenney (GCC)

JCPenney India teams work on merchandising, pricing optimization, and supply chain analytics. A good place to learn classic retail data problems that remain highly relevant globally. Employees here also contribute to demand forecasting and promotions optimization, core levers of profitability in the retail sector.

21. InfoCepts

Focused heavily on data engineering and modernization, InfoCepts helps organizations migrate to modern platforms and architectures. Perfect if you want to build expertise in data pipelines, warehouses, and lakehouses. It also specializes in BI modernization and cloud-native solutions, giving data engineers exposure to end-to-end data lifecycle projects with leading tech stacks.

22. Mahindra Group (GCC)

Mahindra applies analytics to automotive, manufacturing, and connected product data. A unique blend of industry 4.0 and data science, making it great for those curious about IoT and predictive maintenance. Teams here also work on smart mobility, EV analytics, and supply chain optimization, making it an exciting mix of traditional manufacturing and next-gen digital.

23. Target (GCC)

Target India drives demand planning, advertising measurement, and store optimization. Known for its data experimentation culture, it’s a solid choice if you want to see AI embedded in retail ops. The GCC also powers analytics for customer loyalty programs and personalized promotions, providing a chance to work on retail-scale experimentation with millions of shoppers.

24. Polestar (GCC)

The electric car company uses its India hub for connected vehicle data and digital analytics. It’s an exciting place if you’re passionate about mobility, sustainability, and automotive tech. Projects include telematics, driver behavior modeling, and energy efficiency analytics—great for those who want to apply data to the future of green mobility.

25. Indegene

A healthcare-focused firm, Indegene applies analytics to real-world evidence (RWE), omnichannel marketing, and patient support. Excellent for data scientists seeking to impact life sciences and healthcare outcomes. With global pharma and biotech clients, it’s a chance to apply advanced analytics in regulated healthcare settings and directly improve patient experiences.