About this opportunity
Tinder lists this Manager of Analytics (Integrity) opportunity in new york, New York. Review the employer’s description below for duties, qualifications and application requirements.
Job description
The Data Science & Analytics team thrives on data-driven insights to make more informed decisions through our insights into our member’s behavior, preferences, and common trends. We take ownership over the integrity of our data and work to improve data literacy across Tinder
Integrity is where that work meets real-world stakes. Our Integrity organization is built on four product pillars working toward shared outcomes:
Safety Products enhances members’ perception of safety through healthy engagement, safe-dating awareness, and support when something goes wrong — owning reporting and the Safety Center, verification and suspension flows, Face Check and Selfie Challenge, and our respectfulness and IRL safety experiences
Account Integrity secures and qualifies accounts so that each one represents a unique, authentic, qualified individual — while controlling friction, acquisition cost, and privacy. It owns authentication and account access, Passkeys and SMS/OTP, account recovery, and our defenses against account takeover
Anti-Abuse proactively identifies, disrupts, and mitigates adversarial abuse at scale, balancing accuracy against responsiveness — owning scaled-abuse detection, signal analysis, the rules engine, rapid-response mitigations, and enforcement quality
Moderation & Ops keeps Tinder safe, resilient, and compliant through the internal tools, back-end systems, and AI integrations that drive moderation quality, operational efficiency, and data hygiene — including appeals and case tooling, AI moderation, and conversation safety systems
We are seeking a Manager, Analytics to lead the data science function supporting Integrity. You will manage a team of three data scientists spanning a range of seniority — with room to grow it as the space expands — while serving as the analytics partner to the Product Team Leads across all four Integrity pillars
This is a hands-on management role: you will own the analytical strategy for the space, but you are also expected to stay close to the data — leading investigations yourself when the question warrants it, and raising the bar on your team’s work through direct technical mentorship rather than review alone
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
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
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
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
Benefits
Mind & Body: Take care of yourself with benefits to keep you physically and mentally healthy.
Company Perks: As winners of Comparably’s 2022 Best Company Perks and Benefits Award, we’re proud to say we provide perks that make a difference
Life @ Tinder: We support each other— from informal check-ins to snacks + catered lunches at HQ to the flexibility to take time off when you need it
Ability to communicate complex findings clearly, influence cross-functional stakeholders, and prioritize across competing needsExperience providing hands-on technical guidance while managing and developing a teamUnderstanding of classifier evaluation, including precision, recall, threshold selection, and the trade-offs between false positives and false negativesExperience working with large, complex, event-level datasets and modern analytics or business intelligence tools (e.g., Databricks, Tableau, Mode)Bachelor’s, Master’s, or equivalent experience in a quantitative field, such as Statistics, Economics, Mathematics, Computer Science, Data Science, or a related disciplineDeep experience with experimentation and causal inference, including designing approaches for settings where a clean randomized test is not availableExperience in Trust & Safety, fraud, risk, content moderation, or another domain involving sensitive or adversarial behaviour5+ years of experience in data science or analytics, including 2+ years directly managing data scientists or analystsExpert-level SQL and strong working knowledge of Python or R for analysis and modelingStrong product and business judgment, particularly when balancing member protection, member experience, and operational costExperience building or adopting AI-assisted analytics workflows at the team levelExperience partnering with machine learning teams on detection or ranking modelsFamiliarity with global online safety or age assurance regulations and related reporting obligations
#J-18808-Ljbffr
Worksite address
new york, NY, 10261, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.