Founding Data Lead
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Founding Data Lead at MLabs: Jersey City, США; Гібридно; Lead; IT; Аналітика. JobGrid adds normalized role facts, source context, and a path to the employer application page so candidates can compare the listing before applying.
- Location and workplace: Jersey City, США, Гібридно
- Role classification: IT, Аналітика, Lead
- Source freshness: checked by JobGrid on 2026-05-31.
- Application path: candidates continue to the employer application page with non-personal referral tags.
We are hiring on behalf of our client, an elite, venture-backed digital asset infrastructure firm who is seeking a strategic and highly autonomous Founding Data Lead. Backed by top-tier Web3 investors including Paradigm and Dragonfly, the client is building foundational, institutional-grade stablecoin infrastructure and full-service platforms to transform how global value moves.
As the Founding Data Lead, the successful candidate will build the organization’s data and analytics function from the ground up. This role offers high visibility and immense autonomy, with ownership over how data is defined, structured, and utilized across every facet of the business. By mapping data across the entire stack—encompassing onchain, product, financial, and operational data—this individual will translate raw behavioral and transactional metrics into actionable insights that directly shape product development, investment strategies, and growth trajectories.
Key Responsibilities
- Build from Scratch: Establish, scale, and own the data analytics function, infrastructure, and metrics frameworks across the entire organization.
- Cross-Stack Data Mapping: Integrate disparate data sources across onchain activities, product usage, financial transactions, and operations into a cohesive, centralized data model.
- Drive Business Insights: Deepen customer understanding by transforming raw behavioral data into strategic insights that influence product roadmaps and business growth.
- Enable Self-Service Analytics: Design, deploy, and maintain intuitive dashboards and reporting structures (e.g., Metabase, Looker) to empower cross-functional teams to make rapid, independent, data-driven decisions.
- Engineering Partnership: Collaborating closely with the engineering team to optimize data pipelines, implement product analytics tracking, and elevate the capabilities of the data stack.
- Executive Communication: Synthesize complex data findings into clear, high-impact recommendations for the executive leadership team.