Sr. Data Analyst

Who We Are (Mode.
Inc)Mode is a fast-growing technology company building businesses at the intersection of AI, data, mobile apps, and digital experiences. Our portfolio of mobile apps and digital products reaches 100M+ monthly active users across a global audience. We continue to accelerate growth through product innovation, strategic acquisitions, and emerging business opportunities.
Who We Are (Mode.
Inc)Mode is a fast-growing technology company building businesses at the intersection of AI, data, mobile apps, and digital experiences. Our portfolio of mobile apps and digital products reaches 100M+ monthly active users across a global audience. We continue to accelerate growth through product innovation, strategic acquisitions, and emerging business opportunities. Mode was recognized by Deloitte as the #1 fastest-growing software company in North America on the 2023 Technology Fast 500. Today, we are building our next phase of growth, including expanding Mode's AI and data business and developing direct relationships with companies that can benefit from the data and capabilities we have built.
Our Team and Culture Drive Our SuccessOur team is the heart of our culture. We value innovation, collaboration, and curiosity, with a passion for getting things done. We strive to hire and cultivate the best team members and foster a culture of open communication and transparency. We are driven and hard-working but also committed to having fun along the way. We allow OKRs to guide us, assume positive intent, sometimes agree to disagree and commit, honor our commitments, seek to accomplish more with less, and encourage everyone to speak up as our team owns our company's success. You can read more about our team and how we work here.

About the Role
We're looking for a Senior Data Analyst to be the analytical partner to our Monetization team. You'll own how we measure and grow revenue across our portfolio of mobile apps and web properties, spanning subscriptions, in-app purchases, advertising, and partner offers, and turn that into clear recommendations on pricing, packaging, and revenue mix. The ideal candidate has exceptional SQL and Python skills, hands‑on experience with consumer subscription apps, and the rigor to design pricing experiments that hold up.

What You'll Do
Design, build, and maintain common datasets and data pipelines that strengthen self-service analytics and enable data-driven decision making across the organizationImprove data quality, accuracy, reliability, and documentation to strengthen self-service analyticsOwn revenue and monetization metrics across the portfolio, including ARPU/ARPDAU, LTV, trial-to-paid conversion, renewal and churn rates, refunds, and revenue mix by sourceDesign and analyze pricing, packaging, and paywall experiments (price points, trial length, plan structure, paywall placement and copy), and read results with statistical rigorBuild subscription cohort and LTV models that inform pricing decisions and feed back into UA bidding and payback targetsAnalyze ad monetization performance, including eCPM, fill rate, impressions per user, and mediation/bidding setup, and balance ad revenue against retention and user experienceMeasure the economics of partner offers and rewards, including revenue earned vs. rewards paid out, to keep the rewards model profitableReconcile revenue data across app stores, subscription platforms, ad networks, and internal systems, and investigate discrepanciesPartner with Monetization, Product, and GMs on revenue forecasting, opportunity sizing, and roadmap prioritizationCommunicate analytical findings through clear, compelling narratives to drive alignment, inform prioritization, and deliver measurable business impactWhat You Bring to the TeamAnalytical excellence to dissect complex, ambiguous problems and uncover actionable insightsSolid SQL and Python programming skills, and experience working with large-scale production dataBusiness acumen to translate data and analysis into business impactExceptional written and verbal communication skills to effectively collaborate in a highly cross-functional environment4+ years in analytics, preferred background in monetization, pricing, or revenue analytics for consumer subscription apps & gamesExperience with LTV modeling and revenue forecasting on subscription and ad monetized apps/gamesTrack record of designing and interpreting pricing or paywall A/B tests, including pitfalls like novelty effects, long conversion windows, and LTV vs. short-term conversion tradeoffsFamiliarity with app store subscription mechanics (App Store/Google Play billing, trials, grace periods, renewals, refunds) and subscription platforms (e.g., RevenueCat, Superwall, Adapty)Nice to have: experience with ad mediation experience (AppLovin MAX, ironSource/Unity LevelPlay, AdMob), web checkout or web-to-app payments, rewards or loyalty program economics, Big Data tools (Redshift/Spark/Airflow), dashboarding tools (Looker, Tableau), experiment desig