Data Scientist II

2-4 years in data science or analytics with demonstrated business impact. Strong SQL, including complex joins, window functions, CTEs, and query hygiene. Proficiency in Python or R for analysis, experimentation, and reproducible workflows. Working knowledge of statistics: hypothesis testing, experiment design basics, confidence intervals, and regression fundamentals. Experience with BI tools such as Looker or Tableau and building dependable dashboards. Clear written and verbal communication with the ability to explain technical topics to non-technical audiences.

Own and deliver analytics projects end to end: define questions, write SQL, analyze results, and present recommendations. Design and analyze A/B tests and quasi-experiments; document methodologies and learnings. Build and maintain reliable dashboards; define metrics and implement data quality checks. Synthesize data from multiple sources into narratives for reviews; support OKR tracking. Contribute to data models and analytical datasets with data engineering. Document work, follow best practices for reproducibility, and participate in reviews.