The Product Analyst will play a key role in shaping product strategy through rigorous data analysis, experimentation, and statistical evaluation. This role partners closely with product managers, engineers, and designers to uncover insights, validate hypotheses, and drive data‑informed decision‑making across the product lifecycle.
Tasks
You will design and analyze A/B tests, apply advanced statistical methods, and build analytical frameworks that help the team understand user behavior, measure feature impact, and optimize product performance. The ideal candidate brings strong technical skills in Python and SQL, deep knowledge of causal inference techniques, and the ability to translate complex findings into clear, actionable recommendations.
Key Responsibilities
- Analyze product performance, user behavior, and feature adoption to identify opportunities for improvement.
- Design, implement, and evaluate A/B tests, sequential tests, and other experimental frameworks.
- Apply statistical methods—including causal inference and Difference‑in‑Differences (DID)—to measure product impact.
- Build dashboards, reports, and automated analyses to support ongoing product decisions.
- Collaborate with product, engineering, and design teams to define metrics, success criteria, and data requirements.
- Communicate insights clearly to both technical and non‑technical stakeholders.
Requirements
Required Skills & Experience
- Strong proficiency in Python for data analysis (pandas, NumPy, SciPy, statsmodels).
- Solid understanding of statistics, experimental design, and hypothesis testing.
- Hands‑on experience with A/B testing, sequential testing, and DID causal inference methods.
- Strong SQL skills for querying and transforming large datasets.
- Ability to translate analytical findings into actionable product recommendations.
- Experience working in cross‑functional, fast‑paced product teams
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