Data Scientist, Tinder

• Tinder's Growth Data Science team seeks curious individuals eager to drive data-informed decision-making
• The ideal candidate is a creative problem-solver passionate about transforming complex challenges into actionable insights through meticulous data analysis and A/B testing
• Strong communication skills are essential, as you’ll present findings and recommendations to diverse stakeholders, influencing business performance and enhancing user experiences
• Bachelor’s degree in a quantitative field (e.g. Economics, Computer Science, Statistics), Master’s degree or PhD preferred 2-4 years of professional working experience in Data Science and/or analytics
• Experience with SQL, data visualization tools (e.g., Tableau or Mode), and A/B testing is required
• Familiarity with Python/R, using descriptive and inferential statistics and machine learning models
• Ability to develop a nuanced business understanding, testable hypotheses, and significant findings from data
• Ability to present data, actionable insights, technical concepts, and approaches to technical and non-technical audiences

Desirable

• As a strategic partner to the Product team, we use comprehensive datasets to develop experiments, track metrics, automate reports, and generate insights that guide business solutions, impacting business performance and member experience
• This role offers the opportunity to join the User Growth or Growth Platform teams
• The User Growth team validates hypotheses and optimizes core experiences through growth levers and personalization
• In contrast, the Growth Platform team focuses on scaling and optimizing messaging strategies through strategic channels. We'll work closely with you to determine the best team fit
• Tinder seeks a Data Scientist to join our growing Analytics team, powering data-driven decision-making across Product, Marketing, Engineering, and Finance
• In this role, you'll leverage extensive user behavior data to develop experiments, forecasting models, automated reports, and exploratory insights that guide key business strategies
• Drive rigorous testing to validate hypotheses and guide business decisions
• Find the “story” in the data and readily share insights with product, engineering, and design as well as at a company level
• Be an authority with a point of view for the organization, using data to constantly challenge and reshape our current understanding of customer behavior and business performance
• Derive and communicate data-driven recommendations regarding both the prioritization of potential product/marketing initiatives and the performance of current initiatives
• Define and operationalize the detailed tracking of company-wide, team-specific, and product-specific performance metrics via rollout tables, dashboards, and automated reporting