Director, Data & Analytics

MoonPay•New York, NY

7d•$360,000 - $410,000•Hybrid

About The Position

As Director of Data & Analytics, you'll own Product Data & Analytics across Product & Engineering, reporting to the CTO, Ramps & Platform. You'll have a real mandate: build out the team, define how it operates, and make it the reason MoonPay ships better products faster. The metrics, experimentation, and data infrastructure that Product, Engineering, and Leadership rely on to decide what to build next will be yours to shape. This is a builder's role. You'll grow a function spanning Data Science, Analytics Engineering, and Data Analysts, hiring across levels and shaping how these three disciplines work together as one team. You'll set the bar for rigor, design the structure and career paths that let each discipline do its best work, and scale the function alongside one of the fastest-growing companies in crypto. If you've wanted to take a data organization to the next level, with executive backing and a business that genuinely depends on it, this is that opportunity.

Requirements

10+ years of experience in data science, analytics, or analytics engineering, with significant time in a management or leadership role
A track record of building and scaling a data/analytics function from the ground up or through a high-growth phase, including hands-on hiring across multiple disciplines
Deep experience partnering with Product and Engineering teams to embed analytics and experimentation into how products get built
Strong technical fluency across the disciplines you'll manage. You don't need to write production code daily, but you can evaluate tradeoffs in data modeling and experimentation design
Excellent stakeholder management skills, with experience communicating clearly to executives, engineers, and cross-functional partners alike
Experience working within fintech, payments, or crypto is a strong plus
An active interest in cryptocurrency and Web3, and comfort operating in a fast-moving, less-defined environment

Responsibilities

Own the direction, roadmap, and operating model for Product Data & Analytics
Recruit, hire, and lead a team spanning three disciplines: Data Scientists (experimentation, modeling, causal inference), Analytics Engineers (data modeling, self-serve infrastructure), and Data Analysts (product metrics, dashboards, ad hoc analysis)
Design the org structure, leveling, and career paths that let each discipline scale as the team grows
Standardize how product metrics, experimentation, and analytics get built and consumed across MoonPay, replacing one-off analysis with reusable, trusted data products
Partner directly with Product and Engineering leadership to embed analytics and experimentation into the product development lifecycle, from problem definition through post-launch measurement
Set technical and quality standards across the team's work: data modeling conventions, experimentation methodology, dashboarding and reporting practices
Represent data and analytics needs in cross-functional planning with Product, Engineering, Finance, Operations, and Compliance
Mentor team leads and senior ICs, building a bench of future managers within the function
Report on team health, hiring progress, and analytics impact to senior leadership