Executive Summary & Why This Matters
A focused plan for the three months before you start applying, built around the skills Data Scientist employers screen for. In competitive hiring landscapes, small differences in signaling, formatting, and strategic presentation compound into major outcomes. This playbook synthesizes proven hiring insights to help candidates bypass common screening bottlenecks.
- Days 1–30: fundamentals of ‘statistics and probability’ and machine learning with scikit-learn, plus hands-on practice with ‘Python (pandas, scikit-learn)’.
- Days 31–60: build one project using feature engineering and SQL, and write it up.
- Days 61–90: practise interview topics (‘bias-variance and overfitting’ and feature engineering), polish your resume and start applying.
- Study in focused blocks and review weekly; shipping small outputs beats passive watching.
- Measure readiness with mock interviews and ask for feedback on your project.