Overview
Data scientists turn raw data into business decisions and products — building predictive models, A/B tests, recommendation engines, fraud-detection systems and now LLM-powered features. Demand has exploded with the GenAI boom; Indian unicorns and Fortune-500 GCCs (Walmart, JPMC, Goldman) are hiring aggressively, with junior offers crossing ₹15-25L at top firms.
Day-to-day responsibilities
Pull and clean data from warehouses (SQL/Spark); explore distributions and build features; train models in Python (scikit-learn / PyTorch / XGBoost); design and analyse A/B tests; present findings to product and business teams; productionise models with MLOps tooling; monitor live model drift; collaborate with engineers on data pipelines.
Skills required
- Python (NumPy/pandas/scikit-learn)
- SQL (advanced)
- Statistics & probability
- Machine learning fundamentals
- A/B testing & causal inference
- Communication & visualisation
- Big data (Spark) basics
- Cloud notebooks (SageMaker/Vertex)
Education path
Most data scientists hold a master's — MTech in Data Science / Computer Science, MS Statistics, or MBA from IIM with analytics specialisation. Strong B.Tech graduates (especially CS/Maths/Stats) increasingly enter directly via internships. PhD is common at research labs (Microsoft Research, Google Brain India).
Career progression
- 1Data Scientist I
- 2Data Scientist II
- 3Senior Data Scientist
- 4Lead / Staff Data Scientist
- 5Principal DS / Director of Data Science
Top employers in India
Useful certifications
- AWS Machine Learning Specialty
- Google Cloud Professional ML Engineer
- Databricks Certified DS
- IIT-Madras BS in Data Science