Data Science, Tinder

• An effective DS II at Tinder must have a passion and aptitude for turning sophisticated problems into concrete hypotheses that can be answered through meticulous data analysis and A/B testing
• You must be able to disseminate findings and recommendations to a variety of partners across the organization via presentations, reports, and dashboards
• Bachelor’s degree in a quantitative field (e.g. Economics, Computer Science, Statistics), Master’s degree or PhD preferred
• 4+ years of experience in data science or analytics, 1-2 years background in Integrity
• Ability to develop a nuanced business understanding, testable hypotheses, and meaningful findings from data
• 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
• Experienced with SQL and data visualization tools (e.g. Tableau or Mode)
• Substantial experience with and understanding of A/B testing

Desirable

• As a DS II on the Integrity team, you will leverage data and automation to help Tinder solve impactful product and engineering problems such as understanding the impact of our user facing features, and creating metrics to better quantify the user experience
• You will develop frameworks and models for how data should be leveraged in decision making and be a key stakeholder in delivering quantitative tools
• In this role, your insights will influence the performance of our business, the experience of our members, and the direction of analytics at Tinder
• Be a leader 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
• Be a strategic partner for Integrity by identifying high impact analytical problems and finding innovative ways to tackle these problems via data analysis, experimentation, and statistical modeling
• Derive and communicate data-driven recommendations regarding both the prioritization of potential product/engineering initiatives and performance of current initiatives
• Evolve our measurement strategy by identifying novel metrics and measurement approaches to guide product strategy, goals, and experiments
• Conceptualize, develop and maintain dashboards for risk detection and monitoring
• Help set the team direction by driving cross-functional alignment on projects and priorities
• Design and analyze experiments to rigorously test specific hypotheses
• Be a mentor/advisor for other Data Scientists on the Analytics team