Director, Data & Decision Science

We are seeking a Director of Data & Decision Science to serve as the architect of our data ecosystem and the strategic engine behind our portfolio growth. This is a high-accountability "Full-Stack" leadership role designed for a practitioner who is equally comfortable managing a technical engineering team as they are advising on multi-million dollar capital allocations. The primary mission of this role is to provide unrivaled clarity across our portfolio. You will lead a team of three Data Engineers to maintain a high-integrity BigQuery and Looker stack, but your true value lies in your ability to translate that data into deep business insights. You aren't just reporting on what happened; you are identifying the "why" behind performance shifts and providing the quantitative logic for our most critical decisions: which digital products to acquire, which to scale, and which to exit. Employment Type This is a full-time independent contractor position. We are not currently hiring for direct employee positions. Location This is a fully remote position. Work where you perform your best. Key Responsibilities Strategic Decision Science & Portfolio Strategy Shape the portfolio growth roadmap using predictive modeling, forecasting, and scenario planning to guide decisions on acquisitions, scaling, and exits Lead the analytical due diligence for potential acquisitions, rigorously auditing user cohorts, retention curves, and unit economics (LTV, CAC, Payback) to pressure-test commercial viability Partner with Finance and Executive Leadership to define and build the predictive models and scenario logic that power the 3-to-5-year financial and operational outlook Data Engineering & Architecture Architect, build, and govern a scalable, high-integrity BigQuery and Looker ecosystem grounded in Data Lakehouse principles, ensuring a 100% reliable "Source of Truth" for decision-making Lead and mentor your team of 3 Data Engineers to build robust ETL/ELT pipelines and maintain strict data governance standards Portfolio Performance & Optimization Establish a standardized KPI framework to measure performance and enable rigorous benchmarking, identifying efficiency gaps and optimization targets to drive portfolio growth Move beyond reporting "what happened" to diagnosing "why" it happened—prescribing specific actions to Marketing and Product teams to optimize revenue Requirements What You Bring Bachelor’s degree in a quantitative field (Computer Science, Economics, Statistics, Physics, or Engineering) or equivalent professional experience 10+ years of professional experience in Data Engineering, Analytics, or Business Intelligence 3+ years in a senior/lead role, specifically managing technical individual contributors (Data Engineers or Analysts) Expert-level fluency in SQL and the Modern Data Stack (BigQuery & Looker), with the ability to architect schemas and conduct code reviews Demonstrated success applying advanced modeling and scenario planning to M&A and investment strategy, rigorously validating investment logic and unit economics A strong history of collaborating with Finance and Executive Leadership to transform technical insights into clear strategic direction Deep familiarity with the unit economics of Subscription (SaaS) or Mobile App businesses (e.g., churning cohorts, ARPU, ROAS) Excellent problem-solving and communication skills Nice to Have (Preferred Qualifications) Master's degree or higher in a quantitative field Advanced understanding of quantitative methods (Statistics, Econometrics, or Computer Science) Prior experience working within Private Equity, Venture Capital, or Corporate Development environments, specifically supporting due diligence Proficiency in Python or R for advanced statistical modeling and forecasting (extending beyond standard SQL capabilities) Hands-on experience with dbt (data build tool) for managing complex data transformation workflows in a production environment