Data Scientist, Tinder

• Bachelor’s degree in a quantitative field, Master’s degree, or PhD with a social science background preferred
• 2-4 years of professional working experience in Data Science and/or analytics
• Familiarity with two sided consumer ecosystem, specifically in the context of consumer technology
• Experience with SQL, data visualization tools (e.g., Tableau or Mode)
• Hands on experience in designing and implementing experiments (e.g. randomized testing, A/B testing) to drive key product decisions is required
• Familiarity with Python/R, using descriptive and inferential statistics and machine learning models
• Demonstrated ability to collaborate effectively with design, product, and engineering
• Teams to advance key business initiatives from conceptualization to final product delivery
• 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
• Proactive collaborator skilled in engaging with cross-functional teams (Product, Engineering, Machine Learning) to influence decision-making, confidently voicing concerns and alternative perspectives

Desirable

• The Growth Data Science team is looking for curious individuals excited to drive data-informed decision-making at Tinder
• We are a strategic partner to the Product team, and will be using our comprehensive datasets to develop experiments, understand metrics, develop automated reports, and generate exploratory insights to guide our business solutions
• These insights are key in both the performance of our business and the experience of our members
• This role has the opportunity to work on either the User Growth or Growth Platform teams within the Data Science Team
• The User Growth team focuses on validating greenspace hypotheses and optimizing the core experience through growth levers and personalization, while the growth Platform team focuses on optimizing and scaling messaging strategy through strategic channels and personalization
• We will work closely with you to define what team would be the best match
• 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