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CRYDD

How to become a Data Scientist: the complete roadmap

Data scientists answer harder questions than dashboards can — with statistics, experimentation, and models. The analyst's toolkit is the entry; the science is the differentiation.

Roughly 12–18 months, faster from an analyst or STEM background.

Stage_01

Analyst foundations

Skills

  • SQL
  • Python for analysis
  • Visualization and communication

Project

Two published analyses of messy public datasets with clear conclusions.

Stage_02

Statistics and modeling

Skills

  • Inference and experimentation
  • Machine learning fundamentals
  • Feature engineering

Project

Design and analyze an A/B test end to end, documented like a paper.

Stage_03

Scale and specialty

Skills

  • Cloud data platforms
  • Pipelines
  • A domain specialty

Project

Rebuild one project on a cloud data stack with scheduled refreshes.

Where Data Scientists go next

  • Machine Learning Engineer
  • AI Engineer
  • Data Analyst