Senior Data Scientist, Places

We are seeking an entrepreneurial and driven data scientist to identify opportunities to improve retention and help the team evaluate and act on them. This will be a fun role for someone who wants to build data solutions from the ground up and help shape how the entire team uses insights. 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 and can demonstrate sound judgment under uncertainty.
We offer comprehensive medical and dental coverage, $50 a day food delivery budget, equity based employment, a great culture, learning opportunities, unlimited vacation, 12 weeks paid parental leave, and we pay all employees $1,000 a year to go somewhere in the world that they've never been because of our values of human connection, empathy, and curiosity.

Responsibilities
Own the definition and evolution of success metrics for all user facing surfaces, including tradeoffs between short-term and long-term member value.

Define and maintain business metrics, semantic layers, and data models to ensure consistency and trust across the Places team.

Own, in partnership with Data Engineering, the translation of product requirements into scalable, reliable data assets that empower efficient decision-making

Influence product direction by uncovering and translating insights into clear recommendations that shape roadmap prioritization.

Build out a culture of high fidelity experimentation to scale wins quickly

Using visualisations to convey nuance with clarity

AI-native mindset and hands-on experience using LLMs, agents, and modern AI tools to automate analysis, accelerate experimentation, and build scalable decision-support workflows

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.

Familiarity in delivering data products through partnership with Data and product engineering teams.

Strong technical fluency with analytical tools such as SQL and Python, or equivalent experience using data to answer open-ended business questions.

Strong applied statistics background, including hypothesis testing, confidence intervals, power analysis, and causal inference techniques.

Familiarity with modern analytics and experimentation tools

Familiarity with consumer focused apps

Strong in proactive verbal and written communication, ability to convey rigorous statistical concepts to non-experts.

Practical AI fluency and curiosity about how modern AI tools can improve analytical workflows, strategic synthesis, and decision support.

Bonus points for familiarity with optimization of performance marketing efforts