Data Scientist

About the role

We’re looking for a business-minded Data Scientist who pairs strong technical skills with sound judgment about which problems are worth solving. You’ll partner with product, marketing, finance, engineering, and trust & safety to turn ambiguous questions into rigorous analyses, models, and experiments — and then turn the results into decisions.

The problems are real and the data is large: understanding what drives user acquisition, engagement, and retention; improving monetization across ads and subscriptions; measuring the impact of product changes; and helping keep our network safe from fraud and abuse. You’ll own work end to end, from framing the question to landing the recommendation with leadership.

What you’ll do

• Frame the right questions. Work with stakeholders to understand business challenges, spot where data can make a difference, and translate open-ended questions into structured analyses with clear success criteria.
• Find what drives the business. Dig into large, complex datasets to uncover the trends, segments, and behaviors behind user growth, engagement, retention, and revenue.
• Build models that get used. Develop and apply statistical and machine learning methods — predictive models, segmentation, forecasting, causal inference — and evaluate them honestly, including their assumptions and limitations.
• Run and read experiments. Design, analyze, and interpret A/B tests and quasi-experiments that inform product and marketing decisions.
• Define how we measure success. Create meaningful metrics, KPIs, and dashboards that teams rely on to track performance and make trade-offs.
• Tell the story. Turn complex findings into clear, actionable recommendations for technical and non-technical audiences, including senior leadership.
• Raise the bar. Partner with data engineering on reliable data and tracking, build reusable analyses and tools, and help spread analytical best practices across the company.

What we’d like to see

• 4+ years of experience in data science, product or business analytics, or a related quantitative role, with a track record of analyses and models that changed decisions.
• Strong Python and SQL skills for data manipulation, analysis, and modelling on large datasets.
• A solid foundation in statistics, experimentation (A/B testing), and common machine learning techniques — and the judgment to choose the simplest approach that answers the question.
• Ability to structure ambiguous business problems and work independently across multiple priorities in a fast-paced environment.
• Excellent written and verbal communication, including explaining technical concepts to non-technical partners and building compelling visualizations and presentations.
• Experience with BI or product analytics tools (e.g., Tableau, Looker, Mixpanel, or similar).
• A degree in statistics, economics, mathematics, computer science, engineering, or another quantitative field — or equivalent practical experience.

Nice to have

• Experience with a consumer mobile app, subscription, or ad-supported business.
• Causal inference beyond A/B testing (e.g., difference-in-differences, synthetic control, uplift modelling), forecasting, or optimization.
• Experience with Snowflake or another cloud data platform (AWS, GCP, Databricks), and with dbt or similar tooling.
• Exposure to fraud, abuse, or anomaly detection.
• Hands-on use of AI to accelerate analysis or build data products.
• A graduate degree in a quantitative field.

Experience comes in many forms — skills are transferable, and passion goes a long way. We know that diversity makes for the best problem-solving and creative thinking, which is why we’re dedicated to adding new perspectives to the team. If this role excites you but you don’t meet every point above, we’d still love to hear from you.