Senior Analyst, Marketing Analytics

Upside•New York, NY

19h•$130,000 - $150,000•Hybrid

About The Position

Meet Upside: We created Upside to transform brick-and-mortar commerce. Our technology uses the sophistication of online retail—profit measurement, attribution, and incrementality—to provide users with more value on their everyday purchases and brick-and-mortar businesses with new, profitable customers. We’ve helped millions of users earn 2 to 3 times more cashback than any other product, and hundreds of thousands of brick-and-mortar businesses earn measurable profit. Billions of dollars in commerce run through the Upside platform every year, and that value goes directly back to our retailer partners, the consumers they serve, and important sustainability initiatives. The Impact You'll Make: We’re hiring a Senior Analyst, Marketing Analytics to own full-funnel performance insights for Upside’s consumer marketing—from acquisition through engagement, retention, and lifetime value. In this high-impact role, you’ll be a trusted, hands-on strategic partner to our Consumer Marketing team, rolling up your sleeves to dig beneath surface-level reporting and uncover the “why” behind performance across channels, creatives, audiences, promotions and on-site/app experiences. You’ll translate data into clear, compelling stories and recommendations that guide how we invest our marketing dollars, optimize conversion rates, and deepen user engagement over time. You’ll bring a strong B2C marketing analytics toolkit, an experimentation approach, and a startup-ready bias for action—comfortable moving from raw data to dashboards to a point-of-view for senior partners.

Requirements

5+ years of experience in marketing analytics, growth analytics, or similar roles supporting B2C businesses (e.g., marketplaces, apps, e-commerce, subscription, or consumer internet). B2C experience is required; experience with app-based products or mobile user acquisition/lifecycle is a strong plus.
Expert SQL skills and experience working with large, complex marketing and product datasets in modern data warehouses.
Experience working with mobile-first marketing and measurement platforms (e.g., AppsFlyer, Haus), mobile first acquisition channels (e.g. Apple Search Ads, Google UAC, Meta), as well as lifecycle tools (e.g., Braze), to analyze and optimize performance across the full funnel.
Experience building dashboards and reports in BI tools (e.g., Looker, Hex, or similar) that drive action for non-technical partners.
Solid understanding of digital marketing and growth fundamentals across paid media (social, search, app), CRM/lifecycle (email, push, in-app, SMS), and on-site/app conversion funnels, including key metrics like CAC, ROAS, LTV, retention, and engagement.
Hands-on experience with experimentation and testing (A/B tests, multivariate tests, lift studies), including defining success metrics and interpreting results with statistical rigor.
Proven ability to go beyond surface-level reporting—breaking down complex problems, exploring data from multiple angles, and arriving at clear, opinionated recommendations that influence marketing strategy and investment decisions.
Excellent communication and storytelling skills—you can simplify complex quantitative work, tailor your message to marketing partners and executives, and build trust through clear, honest dialogue.
Highly collaborative and low-ego. You enjoy working closely with marketers, diving into messy data, and iterating quickly in a fast-paced startup environment.
Growth mindset, intellectual curiosity, and comfort operating with ambiguity—continually looking for better ways to measure, learn, and drive impact.

Responsibilities

Own end-to-end reporting and insights for the consumer marketing funnel across acquisition and retention: media efficiency, on-site/app conversion, activation, engagement, and long-term retention/LTV.
Independently scope, prioritize, and drive end-to-end analytics projects in partnership with Marketing, from problem framing through recommendation and follow-through.
Build and maintain clear, reliable metrics frameworks for channel, campaign, ad-set and audience performance (e.g., CAC, ROAS, LTV:CAC, conversion rates, retention), ensuring a single source of truth that provides fast, reliable reads on channel mix, creative, audience, and offer performance across all channels
Serve as the primary analytics partner for Consumer Marketing—collaborating with acquisition, brand, and lifecycle teams to translate business questions into analysis, insights and experimentation plans.
Proactively surface insights on creative, audience, and funnel performance, and bring forward recommendations on where to double down, fix, or test next—going well beyond pull-and-paste reporting.
Partner with the senior team members to interpret MMM, attribution, and incrementality outputs, and translate them into channel and funnel-level recommendations and recommend future experients
Partner with lifecycle and product marketing to test and iterate on messaging, sequencing, and surface areas (email, push, in-app, onsite) to improve activation, engagement, and reactivation over time.
Diagnose pockets of under-performance across all areas of consumer growth and identify experiments and optimization levers such as new audience strategies, creative, offer structures, or on-site/app conversion opportunities to improve consumer performance.
Develop automated reporting and alerting to flag significant shifts in performance and funnel health, helping the team respond quickly to risks and opportunities.
Partner with Finance and Consumer team members to align on forecasting, pacing, and performance targets, tying media and lifecycle performance back to profitable, scaled growth and IRR.
Support deeper analytics projects (e.g., cohort and retention analyses, audience segmentation, attribution/measurement deep-dives) in partnership with senior analytics leaders, helping connect detailed findings into clear, executive-ready narratives.
Collaborate with Analytics Engineering, Product, and MarTech partners to improve upstream data assets that power marketing reporting and experimentation (e.g., event tracking, attribution signals, identity stitching, channel taxonomies).