Manager, Product and Marketing Analytics

Overview

Hi, We’re Franki. Going out should feel good — not expensive. Franki is the app that helps people discover great restaurants, get cash back just for going, and earn even more for sharing. We’re building a smarter way to eat, drink, and explore your city — one that helps local restaurants thrive and makes the experience more rewarding for everyone.

We’re a fast-moving, high-ownership team that values creativity and execution. The category is dynamic and fun, and we're building a brand that reflects that energy. If you're the kind of person who has big ideas and makes them happen, we’d love to hear from you.

Franki is looking for a Manager, Product & Marketing Analytics to build and scale the measurement engine behind our growth. You’ll own analytics across product, marketing, and rewards—shaping how we measure performance, run experiments, and optimize incentives like cashback and Adventures/Gigs. In this role, you’ll define our company-wide measurement strategy, lead causal inference and experimentation, and develop predictive models (LTV, churn, MMM, propensity) that guide roadmap, channel mix, and budget decisions.

This is a hands-on, high-influence role blending deep analytical work in SQL/Python with strategic leadership. Your insights will drive repeat behavior, shape reward economics, and ensure we grow efficiently while keeping costs and liabilities within guardrails.

Note:

Candidates residing in our preferred locations; CA will be given first consideration.

• 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.

• 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, stats models, causal inference); experience building scalable dashboards and pipelines in Big Query and Looker.
• Expertise in experimentation design: A/B tests, CUPED, geo/holdouts, power analysis, uplift modeling; familiarity with experimentation platforms like Eppo, Statsig, or Launch Darkly.
• 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.

• Comfortable operating at both altitude (strategy, exec forums) and depth (hands‑on SQL/Python).
• Excellent written storytelling; exec-ready visuals and clear recommendations.
• Ability to manage multiple…