Manager, Analytics (Integrity)

Our Mission As humans, there are few things more exciting than meeting someone new. At Tinder, we’re inspired by the challenge of keeping the magic of human connection alive. With tens of millions of users, hundreds of millions of downloads, 2+ billion swipes per day, 20+ million matches per day, and a presence in 190+ countries, our reach is expansive—and rapidly growing. We work together to solve complex problems. Behind the simplicity of every match, we think deeply about human relationships, behavioral science, network economics, AI and ML, online and real-world safety, cultural nuances, loneliness, love, sex, and more.

Our Values Take the Lead: We don't ghost our work or each other. Just as users don't leave their matches hanging, we don't let each other down. Move Fast: We have a bias for action and urgency. Something that could be done tomorrow would be better if done today. Better Together: We keep connection at the heart of dating and at the heart of how we work. Just as our users are better when they connect with others, so are we when we collaborate. Real Talk: We say the hard thing the human way. Just as we ask our users to behave with kindness and candor in our community, we expect Team Tinder to do the same. Safety First: We act with integrity, transparency, and consistency so people feel safe—whether they're swiping, matching, or working alongside us. Spark Fun: We have fun to unlock creativity, fuel innovation, and help us build better experiences for daters.

Lead and Develop a Team of Data Scientists Manage, coach, and grow a team of data scientists supporting the Integrity organization, owning hiring, career development, and performance. Set clear ownership across the four pillars and balance your team's capacity against competing roadmap and escalation demands. Raise analytical quality through hands-on technical mentorship — reviewing methodology, pairing on complex analyses, and unblocking your team on ambiguous problems. Serve as the Analytics Partner to Integrity Product Leadership Act as the primary data science partner to the Product Team Leads for Safety Products, Account Integrity, Anti-Abuse, and Moderation & Ops. Shape roadmaps by sizing opportunities, pressure-testing hypotheses, and defining what success looks like before work starts. Translate ambiguous safety and abuse problems into tractable analytical questions with clear decision criteria. Stay Hands-On with the Data Personally lead high-stakes or highly ambiguous investigations — abuse pattern shifts, enforcement anomalies, unexpected regressions in member experience. Build and maintain the analytical frameworks the team relies on: prevalence measurement, enforcement precision and recall, appeal and reversal rates, moderation queue throughput and quality. Retain deep fluency in the underlying data so that your reviews, estimates, and escalations are grounded in the data itself. Own Measurement and Experimentation for Integrity Define the metrics that govern Integrity's trade-off between protection and member experience, and hold the organization to them. Guide experimental design and interpretation for interventions where classic A/B testing is hard — low-prevalence outcomes, adversarial populations, and changes that cannot be ethically withheld. Establish causal measurement approaches for enforcement actions, verification challenges, and moderation policy changes. Translate Insights into Executive-Level Narratives Synthesize complex analyses into clear recommendations for Product, Engineering, Legal, Policy, and executive leadership. Support regulatory, transparency, and external reporting obligations with defensible numbers and clearly documented methodology. Influence decisions through structured communication, framing insights in terms of member impact, risk, and trade-offs.

Bachelor’s, Master’s, or equivalent experience in a quantitative field, such as Statistics, Economics, Mathematics, Computer Science, Data Science, or a related discipline. 5+ years of experience in data science or analytics, including 2+ years directly managing data scientists or analysts. Expert-level SQL and strong working knowledge of Python or R for analysis and modeling. Deep experience with experimentation and causal inference, including designing approaches for settings where a clean randomized test is not available. Experience working with large, complex, event-level datasets and modern analytics or business intelligence tools (e.g., Databricks, Tableau, Mode). Understanding of classifier evaluation, including precision, recall, threshold selection, and the trade-offs between false positives and false negatives. Experience providing hands-on technical guidance while managing and developing a team. Experience in Trust & Safety, fraud, risk, content moderation , or another domain involving sensitive or adversarial behavior. Strong product and business judgment, particularly when balancing member protection, member experience, and operational cost. Ability to communicate complex findings clearly, influence cross-functional stakeholders, and prioritize across competing needs.

Familiarity with global online safety or age assurance regulations and related reporting obligations. Experience partnering with machine learning teams on detection or ranking models. Experience building or adopting AI-assisted analytics workflows at the team level.

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