As a Data Scientist on the Core Engagement team, you will collaborate with our cross-functional teams to develop and execute product roadmaps, and define/own the ways we measure success and elevate the experimentation capabilities of the team.
We are seeking an entrepreneurial and driven data scientist to accelerate our efforts and play a significant role in our data-centric culture. This person should be able to articulate best practices, develop new analytical frameworks that can tie user actions with output metrics and strike the right balance between analytical rigor and pragmatic business action.
This person will work closely with various cross-functional teams, such as product, engineering, and design, to develop and deliver metrics, analyses, solutions, and insights.
Successful candidates will demonstrate technical skills, product expertise, business acumen, and be enthusiastic about making a positive impact through timely execution. You are passionate about leveraging the power of data to drive product changes with quality and agility.
Your Responsibilities Will Include- Design, evaluate, and interpret experiments in the presence of network effects, delayed outcomes, and imperfect randomization—balancing speed with statistical rigor.
- Influence product direction by translating insights into clear recommendations that shape roadmap prioritization.
- Develop key strategic insights through exploratory data analysis, to inform future investments or pivot in strategy
- Build scalable metrics and dashboards to empower efficient decision-making
- Own the definition and evolution of success metrics for core engagement surfaces, including tradeoffs between short-term and long-term member value.
Qualifications- 5+ years of data science and product analytics experience
- BS and/or MS in a quantitative discipline: statistics, operations research, computer science, engineering, applied mathematics, physics, economics, etc.
- Experience in designing trustworthy experimentation and analyzing complex product a/b testing results
- Expert in SQL, including complex joins, window functions, and performance-aware querying on large datasets
- Expert in Python or R programming, including common scientific computing packages and data science tools such as NumPy, Pandas, and Scikit-learn
- Strong applied statistics background, including hypothesis testing, confidence intervals, power analysis, and causal inference techniques
- Familiarity with modern analytics and BI tools like Looker, Tableau, Omni, Hex, Sigma, Eppo, StatSig, etc is a plus
- A strong understanding of two-sided marketplace dynamics
- Experience in navigating eco-system effects is a plus
- Strong in proactive verbal and written communication and presentation skills, ability to convey rigorous statistical concepts to non-experts
- Strong strategic thinking to navigate a complex business problem, going beyond short-term optimization. You excel at understanding the deeper “why” behind data insights
- Eagerness to explore and apply AI and emerging technologies (e.g., LLMs, automation, intelligent tooling) to accelerate analysis, experimentation, and decision-making
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