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. This is an early, foundational hire on the Core Engagement team. You will help establish the analytical and data foundations that the team—and broader company—will rely on, before transitioning into a full-stack product data science role as those foundations mature.
We are seeking an entrepreneurial and driven data scientist to accelerate our efforts and play a significant role in shaping how data is used to drive forward the business. This will be a fun role for someone who wants to build data solutions from the ground up and help shape how the entire company uses insights. Someone who can make deliberate tradeoffs between speed and completeness when building foundational data assets, ensuring the team can move quickly without compromising long-term integrity.
An ideal candidate has operated as both a Data Scientist and an Analytics Engineer or Data Analyst, and is comfortable moving between foundational data work and product-facing analysis. This person should be able to articulate best practices, develop new analytical frameworks that tie user actions to outcomes, and strike the right balance between analytical rigor and pragmatic business action.
Successful candidates will demonstrate technical skills, product expertise, and 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
Own the definition and evolution of success metrics for core engagement surfaces, including tradeoffs between short-term and long-term member value.Define and maintain core engagement metrics, semantic layers, and data models to ensure consistency and trust across the organization.Own, in partnership with Data Engineering, the translation of product requirements into scalable, reliable data assets.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 strategyBuild scalable metrics and dashboards to empower efficient decision-making
Qualifications
5+ years of data science and product analytics experienceBS 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 resultsFamiliarity in delivering data products through partnership with Data and product engineering teamsVery strong SQL skills, including complex joins, window functions, and performance-aware querying on large datasets.Very strong in Python or R programming, including common scientific computing packages and data science tools such as numpy, pandas, and scikit-learnStrong applied statistics background, including hypothesis testing, confidence intervals, power analysis, and causal inference techniques.Familiarity with modern analytics and experimentation tools like Looker, Tableau, Omni, Hex, Sigma, Eppo, StatSig, etc is a plus Strong in proactive verbal and written communication, ability to convey rigorous statistical concepts to non-expertsEagerness to explore and apply AI and emerging technologies (e.g., LLMs, automation, intelligent tooling) to accelerate analysis, experimentation, and decision-making.