As a Senior Data Analyst at Prizeout, you will analyze consumer behavior, build models, report insights, and collaborate across teams to enhance user engagement and product strategies.
What is Prizeout
Prizeout is a fast-growing fintech transforming how people interact with their money by turning everyday transactions into rewarding, value-driven moments. We sit at the intersection of payments, rewards, and loyalty, empowering financial institutions to build deeper connections with their users. Our platform analyzes rich transactional data to deliver personalized insights and maximize value with every purchase. The company was founded in 2019 and is headquartered in NYC.
Why Prizeout
At Prizeout, we’re redefining how people engage with their money through smarter, data-driven rewards. We’re looking for curious, analytical builders who love turning complex, messy data into meaningful insights that drive loyalty and better financial outcomes. We keep the user at the center of every decision and we value humility, curiosity, and ownership.
About This Role
As a Senior Data Analyst, you’ll drive insight across the lifecycle of CashBack+ Pay (our app for credit union members to use in person or online). You will analyze how members discover, download, and use Pay, to help improve conversion funnels, marketing effectiveness, outcomes, and the payment experience. You’ll build analytical models, uncover behavioral insights, and partner cross-functionally to shape product strategy and growth experiments. This is a high-impact role for someone who loves turning complex behavior into clarity and is motivated by improving real people’s everyday financial lives.
What You'll Do
- Analyze the full Pay funnel from awareness, through activation, to long-term loyalty.
- Build frameworks and develop attribution models to understand what drives user acquisition and conversion
- Quantify key activation milestones (e.g., deposit health signals, card linking, first gift card purchase, streaks)
- Surface insights on shopping patterns, merchant experience quality, and cashback/offer behavior
- Work cross-functionally to define KPIs, test hypotheses, and evaluate A/B experiments
- Partner with data leadership to build meaningful reporting, dashboards, and retention/engagement benchmarks
- Identify friction points in the Pay experience and recommend product, UX, or marketing optimizations
- Support GTM and partner teams with analytics to drive adoption, engagement, and growth
- Translate complex findings into actionable narratives and recommendations for senior stakeholders
What We're Looking For
- 3+ years in data analysis, product analytics, or quantitative roles (startup or fintech experience a plus)
- Experience with funnel analytics, cohort analysis, retention modeling, and A/B testing
- Proficiency in SQL, Python, BI tools (Tableau/Looker), and Excel
- Ability to organize ambiguity and clearly communicate the “so-what”
- Comfort working with transaction data, behavioral signals, and marketplace or consumer app metrics
- Desire to influence the product direction and growth strategy through deep user understanding
- Must be able to work 2-3 days/week in our NYC office.
- Must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment visa at this time.
Please Note:
The expected salary range for this position is $115,000-$130,000, plus an equity component.
Prizeout is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Top Skills
Excel
Looker
Python
SQL
Tableau
Prizeout New York, New York, USA Office
Union Square offers some of the best restaurants, fitness studios, and outdoor space the city has to offer. In addition to that, there are various subway trains and it is a quick walk to Penn Station or train to Grand Central.
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