Tinder is looking to optimize its recommendations algorithm and drive initiatives that impact member engagement and revenue by hiring a Senior Data Scientist to work closely with the Recommendations Product team.
Requirements
4+ years of validated experience in data science or analytics, preferably on user-facing consumer experiences
Ability to develop a multifaceted business understanding, testable hypotheses, and meaningful findings from data
Experienced with SQL and data visualization tools (e.g. Tableau or Mode)
Proficient in Python or R
Meaningful experience with and understanding of A/B testing and advanced statistical techniques
Experience with recommendation products is a plus
Responsibilities
Design and analyze experiments for Tinders core recommendations and ML to rigorously test specific hypotheses
Define and operationalize the detailed tracking of company-wide, team-specific, and product-specific performance metrics via rollup tables, dashboards, and automated reporting
Derive and communicate data-driven recommendations regarding both the prioritization of potential product/marketing initiatives and performance of current initiatives
Be an authority with a point of view for the organization and the team, using data to constantly challenge and reshape our understanding of customer behavior and business performance
Find the story in the data and share insights across the organization
Enhance a comprehensive dataset of user behaviors to develop experiments, predictive models, automated reports, and various exploratory user insights to guide our business decisions
Be a mentor/advisor for other Data Scientists on the Analytics team
Other
Bachelors degree in a quantitative field (e.g. Economics, Computer Science, Statistics), Masters degree or PhD preferred
Eagerness to identify and explore new product/marketing opportunities, potential improvements to our data infrastructure, and unanswered questions about customer behavior
Outstanding written and verbal communication skills, and a willingness to collaborate with business partners
Be an authority with a point of view for the organization and the team
Be a mentor/advisor for other Data Scientists on the Analytics team
