Manager, Analytics (Integrity)

Matchgroup
New York, NY
Hybrid

Who this role is best for

Geared toward candidates with strong technical and leadership capabilities, comfortable with high-stakes data investigations and shaping product roadmaps.

Best fit for

  • Candidates with advanced quantitative degrees and experience managing data science teams
    — “Bachelor’s, Master’s, or equivalent experience in a quantitative field”
  • Individuals with hands-on technical mentorship experience and fluency in SQL and Python
    — “Expert-level SQL and strong working knowledge of Python or R”
  • Candidates who have shaped product roadmaps through analytical insights and hypothesis testing
    — “Shape roadmaps by sizing opportunities, pressure-testing hypotheses”

Things to consider

  • This role involves significant responsibility for high-stakes investigations and decision-making
    — “Personally lead high-stakes or highly ambiguous investigations”
  • Candidates must be prepared to balance member protection with user experience and operational cost
    — “Strong product and business judgment, particularly when balancing member protection, member experience, and operational cost”

How to stand out

  • Highlight experience in defining metrics for enforcement actions and policy changes
    — “Define the metrics that govern Integrity's trade-off between protection and member experience”
  • Demonstrate expertise in causal measurement and experimental design for non-traditional settings
    — “Designing approaches for settings where a clean randomized test is not available”
  • Showcase ability to translate complex analytical findings into clear executive narratives
    — “Synthesize complex analyses into clear recommendations for executive leadership”
  • Emphasize experience with large-scale event-level datasets and modern analytics tools
    — “Experience working with large, complex, event-level datasets and modern analytics or business intelligence tools”
  • Demonstrate familiarity with classifier evaluation and trade-offs between false positives and negatives
    — “Understanding of classifier evaluation, including precision, recall, threshold selection”
Pace · SteadyCollaboration · HighAutonomy · HighDecision Impact · Company

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Led and developed a team of data scientists
  • Defined metrics for Integrity's trade-off between protection and member experience
Typical background
Experience in leading and managing data science teams

Skills & requirements

Required

Data ScienceTeam ManagementAnalytical FrameworksExperimentationData Quality

Preferred

AI And MLNetwork Economics

Stack & domain

Data ScienceTeam ManagementAnalytical FrameworksExperimentationMetricsCommunicationTeamworkProblem SolvingDecision MakingAnalyticsIntegritySafety

About the role

Original posting from Matchgroup via Lever

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.

In this role, you will::

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Lead and Develop a Team of Data Scientists

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Manage, coach, and grow a team of data scientists supporting the Integrity organization, owning hiring, career development, and performance.

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Set clear ownership across the four pillars and balance your team's capacity against competing roadmap and escalation demands.

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Raise analytical quality through hands-on technical mentorship — reviewing methodology, pairing on complex analyses, and unblocking your team on ambiguous problems.

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Serve as the Analytics Partner to Integrity Product Leadership

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Act as the primary data science partner to the Product Team Leads for Safety Products, Account Integrity, Anti-Abuse, and Moderation & Ops.

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Shape roadmaps by sizing opportunities, pressure-testing hypotheses, and defining what success looks like before work starts.

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Translate ambiguous safety and abuse problems into tractable analytical questions with clear decision criteria.

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Stay Hands-On with the Data

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Personally lead high-stakes or highly ambiguous investigations — abuse pattern shifts, enforcement anomalies, unexpected regressions in member experience.

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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.

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Retain deep fluency in the underlying data so that your reviews, estimates, and escalations are grounded in the data itself.

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Own Measurement and Experimentation for Integrity

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Define the metrics that govern Integrity's trade-off between protection and member experience, and hold the organization to them.

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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.

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Establish causal measurement approaches for enforcement actions, verification challenges, and moderation policy changes.

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Translate Insights into Executive-Level Narratives

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Synthesize complex analyses into clear recommendations for Product, Engineering, Legal, Policy, and executive leadership.

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Support regulatory, transparency, and external reporting obligations with defensible numbers and clearly documented methodology.

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Influence decisions through structured communication, framing insights in terms of member impact, risk, and trade-offs.

You’ll need::

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.

Nice to have::

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.

Compensation:

The salary range for this position is $145,000 - $210,000.  Factors such as scope and responsibilities of the position, candidate's work experience, education/training, job-related skills, internal peer equity, as well as market and business considerations may influence base pay offered. This salary range is reflective of a position based in New York, Los Angeles, OR Dallas. This salary will be subject to a geographic adjustment (according to a specific city and state), if an authorization is granted to work outside of the location listed in this posting.

Los Angeles, CA: $171,000 - $200,000

New York, NY: $179,000 - $210,000

Dallas, TX: $145,000 - $161,5000

As a full-time employee, you’ll enjoy:

Flexible Vacation, 10 Sick Days

Time off to volunteer and charitable donations matched up to $15,000 annually 

Comprehensive health, vision, and dental coverage

100% 401(k) employer match up to 10%, Employee Stock Purchase Plan (ESPP)

100% paid parental leave (including for non-birthing parents) and family forming benefits

Investment in your development: mentorship through our MentorMatch program, access to 6,000+ online courses through Udemy, and an annual $3,000 stipend for your professional development

Investment in your wellness: access to mental health support via Modern Health, paid concierge medical membership, pet insurance, fitness membership subsidy, and commuter subsidy

Free subscription to Tinder Gold

Commitment to Inclusion

At Tinder, we don’t just accept difference, we celebrate it. We strive to build a workplace that reflects the rich diversity of our members around the world, and we value unique perspectives and backgrounds. Even if you don’t meet all the listed qualifications, we invite you to apply and show us how your skills could transfer. Tinder is proud to be an equal opportunity workplace where we welcome people of all sexes, gender identities, races, ethnicities, disabilities, and other lived experiences. Learn more here: https://www.lifeattinder.com/dei

If you require reasonable accommodation to complete a job application, pre-employment testing, or a job interview or to otherwise participate in the hiring process, please speak to your Talent Acquisition Partner directly.

#Tinder

Source: Matchgroup careers (Lever)

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