05 · Data & AI
Data Scientist / ML Engineer
Build models that predict, classify and generate
- Fresher (India)
- ₹5 – 10 LPA
- Demand
What it is
A data scientist finds patterns and builds predictive models; an ML engineer puts those models into production so an app can actually use them. Both need real maths — probability, statistics and linear algebra — not just library calls.
What you actually do all day
- 1Frame a business problem as an ML problem
- 2Engineer features, train and evaluate models
- 3Deploy models as APIs and monitor drift
- 4Increasingly: build on top of LLMs and RAG pipelines
Core tech stack
Core
- Python
- pandas
- scikit-learn
- SQL
Deep learning
- PyTorch
- TensorFlow
- Hugging Face
Production
- FastAPI
- Docker
- MLflow
- Cloud
Reality check: Few companies hire freshers directly as data scientists — many enter via analyst roles.
Good fit if: You genuinely enjoy maths and can sit with an experiment that fails ten times.
Your first step
Do one end-to-end project: raw data → trained model → deployed API anyone can call.