Career transition
Data Analyst to Data Scientist
Analysts already know how to question data and explain results. The transition adds stronger statistics, modeling, and experiment design.
What already transfers
- SQL
- Dashboards
- Business context
- Data cleaning
- Stakeholder communication
Likely gaps
- Statistical inference
- Experiment design
- Machine learning
- Model validation
Do not waste time relearning
- Basic spreadsheet/data literacy
- Visualization basics you already use
Suggested progression
- Python for analysis
- Statistics refresh
- Experiment design
- Supervised learning
- Decision-focused project
Readiness evidence
- A project with assumptions and uncertainty
- A baseline model comparison
- A recommendation tied to a decision
Related learning
Turn this into today's learning plan.
Roe turns an outcome into the next useful lesson, then checks and reviews what sticks.
