Manager, Product and Marketing Analytics

About the Role

The role is part of a fast-moving, high-ownership team that values creativity and execution. The category is dynamic and fun, and the company is building a brand that reflects that energy. If you're the kind of person who has big ideas and makes them happen, this could be the ideal opportunity for you.

Franki is committed to building a smarter way to eat, drink, and explore your city, and the analytics team plays a vital role in achieving this goal. By leveraging data insights and experimentation, the company can optimize its product and marketing strategies, drive growth, and ensure a rewarding experience for its users.

What You Will Do

• Lead the end-to-end analytics program across product, marketing, and rewards, setting the measurement strategy and operating model for the company
• Build and maintain source-of-truth dashboards, core metrics, and instrumentation standards in partnership with Data Engineering
• Run robust experimentation at scale—A/B tests, geo/holdouts, matched markets—and drive causal measurement using CUPED, uplift modeling, and other advanced methods
• Own funnel, cohort, retention, and rewards analytics (cashback, Adventures/Gigs, action incentives); identify leaks, quantify opportunities, and propose optimized reward structures
• Stand up omnichannel marketing measurement across lifecycle, partners/affiliates, paid social/search, and influencers; lead incrementality and attribution frameworks
• Develop LTV, payback, forecasting, and rewards economics models to guide roadmap, budget allocation, portfolio mix, and CAC/LTV guardrails
• Publish weekly and monthly executive readouts with decision-ready insights; influence prioritization, staffing, and budget decisions
• Ensure data quality and integrity through tracking requirements, validation, anomaly detection, and fraud/abuse monitoring (velocity, collusion, partner attribution, CPA integrity)
• Build self-serve semantic layers and Looker dashboards that enable teams to independently answer key questions

What We Are Looking For

• BS/BA in a quantitative field (Statistics, Economics, Computer Science, Engineering, Data Science) or equivalent; MS a plus
• 3+ years in product, growth, or marketing analytics, incentives/loyalty analytics, or data science, with 1+ years in a lead or ownership role
• Advanced SQL and Python (pandas, statsmodels, causal inference); experience building scalable dashboards and pipelines in BigQuery and Looker
• Expertise in experimentation design: A/B tests, CUPED, geo/holdouts, power analysis, uplift modeling; familiarity with experimentation platforms like Eppo, Statsig, or LaunchDarkly
• Strong analytics and modeling skills: LTV, propensity, churn/survival, MMM, budget/payout optimization, and causal inference methods
• Product and marketing analytics experience: funnels, retention, cohorting, lifecycle measurement, attribution, channel mix/ROAS, and audience targeting
• Strong product sense with the ability to translate complex data insights into clear, actionable recommendations that drive product and growth decisions

Nice to Have

• Experience with cloud-based data platforms and tools
• Familiarity with machine learning algorithms and their applications in analytics
• Certification in data science or a related field
• Experience working in a fast-paced, dynamic environment with multiple stakeholders

Benefits and Perks

• Competitive compensation package
• Opportunities for professional growth and development
• Flexible working hours and remote work options
• Access to cutting-edge tools and technologies
• Collaborative and dynamic work environment
• Comprehensive health and wellness benefits
• Generous paid time off policy
• Employee recognition and rewards program
• Professional development and training opportunities
• Flexible spending accounts for healthcare and childcare

• Develop a strong portfolio that showcases your analytics and experimentation skills, including examples of successful projects and insights you've driven.
• Be prepared to walk through your technical skills, including SQL, Python, and experimentation design, and provide specific examples of how you've applied these skills in previous roles.
• Research the company and its products, and be ready to discuss how you can contribute to its mission and goals.
• Practice communicating complex data insights in a clear and actionable way, using examples from your experience.
• Consider learning more about the company culture and values, and be prepared to discuss how you align with them.
• Prepare to talk about your experience with data quality and integrity, and how you ensure the accuracy and reliability of your insights.
• Be ready to discuss your experience with stakeholder management, and how you communicate insights and recommendations to non-technical stakeholders.