Manager, Analytics – Integrity

Match Group

. Manage, coach, and grow a team of three data scientists supporting the Integrity organization .

Posted 9/22/2026full-timeUnited StatesMid-LevelSenior💰 $179,000 - $210,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data science leadership, including team management, technical mentorship, and hands-on analysis. Proficient in SQL, Python or R, and experienced in causal inference and experimentation within Trust & Safety domains.

Highest-signal resume keywords

Expert-Level SQLPython Or R For AnalysisCausal Inference And ExperimentationData Science Team ManagementExperience In Trust & Safety

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ScienceAnalyticsStatistical AnalysisExperimental DesignCausal MeasurementClassifier EvaluationData AnalysisQuantitative ResearchEvent-Level DatasetsTechnical Guidance

Soft Skills

CommunicationInfluencing StakeholdersTeam DevelopmentProblem SolvingProduct Judgment

Tools & Technologies

DatabricksTableauModeAI-Assisted Analytics Workflows

Industry Keywords

Trust & SafetyFraudRisk ManagementContent ModerationOnline Safety RegulationsMember ExperienceOperational Cost

Tech Stack

Tools & technologies

PythonSQLTableau

About the role

Key responsibilities & impact

Manage, coach, and grow a team of three data scientists supporting the Integrity organization
Own hiring, career development, and performance management
Set clear ownership across four Integrity pillars and balance team capacity against roadmap and escalation demands
Provide hands-on technical mentorship by reviewing methodology, pairing on complex analyses, and unblocking ambiguous problems
Serve as the primary data science partner to Product Team Leads for Safety Products, Account Integrity, Anti-Abuse, and Moderation & Ops
Shape product roadmaps by sizing opportunities, pressure-testing hypotheses, and defining success criteria
Translate ambiguous safety and abuse problems into tractable analytical questions
Lead high-stakes investigations into abuse pattern shifts, enforcement anomalies, and member-experience regressions
Build and maintain analytical frameworks for prevalence, enforcement precision and recall, appeal and reversal rates, and moderation queue throughput and quality
Define Integrity metrics governing protection-versus-member-experience trade-offs
Guide experimental design and interpretation for low-prevalence, adversarial, or ethically constrained interventions
Establish causal measurement approaches for enforcement actions, verification challenges, and moderation policy changes
Synthesize analyses into recommendations for Product, Engineering, Legal, Policy, and executive leadership
Support regulatory, transparency, and external reporting with defensible numbers and documented methodology
Influence decisions through structured communication focused on member impact, risk, and trade-offs

Requirements

What 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
2+ years directly managing data scientists or analysts
Expert-level SQL
Strong working knowledge of Python or R for analysis and modeling
Deep experience with experimentation and causal inference, including approaches where a clean randomized test is unavailable
Experience with large, complex, event-level datasets
Experience with modern analytics or business intelligence tools such as Databricks, Tableau, or Mode
Understanding of classifier evaluation, including precision, recall, threshold selection, and false-positive/false-negative trade-offs
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 when balancing member protection, member experience, and operational cost
Ability to communicate complex findings clearly, influence cross-functional stakeholders, and prioritize 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

Benefits

Comp & perks

Flexible Vacation
10 Sick Days
Time off to volunteer
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
Family forming benefits
MentorMatch mentorship program
Access to 6,000+ online courses through Udemy
Annual $3,000 professional development stipend
Mental health support via Modern Health
Paid concierge medical membership
Pet insurance
Fitness membership subsidy
Commuter subsidy
Free subscription to Tinder Gold