Manager, Product and Marketing Analytics

Franki is an innovative app that helps people discover great restaurants while earning cash back. The Manager of Product and Marketing Analytics will lead the analytics program across product, marketing, and rewards, shaping measurement strategies and optimizing incentives to drive growth.

Responsibilities:

• 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

Requirements:

• 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
• 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 high‑stakes initiatives simultaneously; thrive in a fast‑paced startup
• Collaborate effectively across time zones