What You'll Do:

- Data Analysis: Perform attribution analysis, user segmentation, and funnel diagnostics based on behavioral logs; deliver actionable strategy recommendations

- A/B Testing: Assist in experiment design, write SQL queries for data extraction, conduct significance testing, and produce A/B test reports

- Strategy Documentation: Contribute to PRDs for frequency capping, ranking, and content strategy

- Ranking Optimization: Collaborate with algorithm teams on parameter tuning and effect validation

- Label/Tag Development: Organize and refine content/label taxonomies to bridge signals to recommendation systems

What We're Looking For:

Must-Haves:

Proficient in SQL – able to independently extract and analyze data from data warehouses

Solid understanding of basic statistics (hypothesis testing, confidence intervals, A/B testing)

Familiar with Python (pandas) or similar data analysis tools

Knowledge of basic recommender system concepts (CTR/CVR, explore-exploit)

Structured thinking and clear writing skills

Nice-to-Haves:

Prior experience in recommendation systems, growth, or user operations projects

Hands-on experience with A/B testing

Basic understanding of Web3 / crypto concepts

Experience with machine learning projects