Back to Career Center
Career Mastery Center
Data Scientist
Data Scientists analyze large complex datasets, build predictive machine learning models, and deploy AI algorithms to drive automated decision making.
Entry Level (0-2 Yrs)
₹8 - ₹15 LPA
Mid-Level (3-5 Yrs)
₹18 - ₹32 LPA
Senior Level (6+ Yrs)
₹35 - ₹70+ LPA
Arranged Step-by-Step Career Roadmap
Follow this structured phase-by-phase execution plan to achieve your target role.
Phase 1
⏱ Months 1 - 3Mathematics, Statistics & Python
Master Linear Algebra, Probability, Statistics, SQL querying, and Python libraries (NumPy, Pandas).
Key Milestones & Deliverables:
Complete 5 Kaggle EDA notebooks
Master SQL complex joins & window functions
Statistics & Hypothesis testing
Phase 2
⏱ Months 4 - 6Machine Learning Algorithms
Implement Supervised & Unsupervised learning models: Regression, Decision Trees, Random Forests, XGBoost, and Clustering.
Key Milestones & Deliverables:
Train ML models with Scikit-Learn
Model tuning & cross-validation
Build predictive customer churn project
Phase 3
⏱ Months 7 - 9Deep Learning & NLP / LLMs
Explore Neural Networks, PyTorch/TensorFlow, Computer Vision, and Large Language Models (LLMs).
Key Milestones & Deliverables:
Train CNN/RNN image classifier
Fine-tune open-source LLMs
Deploy model API using FastAPI & Docker
Phase 4
⏱ Months 10 - 12Portfolio & Data Science Placement
Publish your ML projects on GitHub, write technical case studies, and apply for Data Scientist & ML Engineer roles.
Key Milestones & Deliverables:
Complete 2 end-to-end ML production projects
Kaggle Grandmaster / Competitions
Apply for referral roles
Essential Technical Skills
Python & RSQL & BigQueryScikit-Learn & TensorFlowExploratory Data AnalysisTableau & PowerBI
Top Hiring Companies
AmazonSwiggyFlipkartFractal AnalyticsMu SigmaMcKinseyGoogle AI