Manager, Strategic Third-Party Data Acquisition

Gen•New York, NY

21h

About The Position

Manager, Strategic Third-Party Data Acquisition Role Overview The Sr. Manager, Strategic Third-Party Data Acquisition will own the strategy, evaluation, and execution of external data partnerships that power our decisioning, analytics, and growth initiatives. This role focuses on strategic data acquisition, data quality and value assessment, and third-party vendor relationship management to unlock new revenue opportunities and improve marketplace performance. You will lead the end-to-end lifecycle of third-party data—from sourcing and evaluation through integration and performance measurement—while partnering closely with data science, risk, product, finance, legal, and procurement. This role manages and mentors a small team of analysts/data scientists and has highly visibility with in the enterprise due to being part of a team working towards the next level of competitiveness.

Requirements

Graduate degree (Master’s or PhD) in engineering, statistics, economics, applied mathematics, computer science, or a closely related quantitative field.
Demonstrated experience in strategic third-party data acquisition and vendor/bureau management in data-rich domains (e.g., financial services, risk, marketing, marketplaces).
Proven background in bureau archiving, off-line analytics, and rapid predictive model development to evaluate new data.
Hands-on experience defining the value of data using robust analytical and economic frameworks.
Experience defining, implementing, or modifying business models and decision algorithms that incorporate third-party data.
Familiarity with modern rapid test platforms such as Eppo, GrowthBook, Optimizely, or VWO (or equivalent) to validate data-driven strategies.
Strong working knowledge of decision systems and real-time data acquisition (APIs, event streams, batch feeds).
Advanced proficiency in analytics and modeling tools (e.g., SQL, Python/R) for data evaluation and model development.
Excellent communication skills with the ability to translate complex analytical insights into clear business narratives and recommendations.
Proven track record of cross-functional collaboration and influencing senior stakeholders.

Nice To Haves

Experience with credit bureaus, identity verification providers, ad-tech/mar-tech data, or similar external data ecosystems.
Prior responsibility for contract negotiation support, including sizing, forecasting, and scenario modeling for vendor agreements.
Familiarity with regulatory and compliance considerations related to consumer and third-party data, working knowledge of FCRA and GLBA.
Prior people management and mentoring experience in analytics, risk, or data science teams.
Comfort working in fast-paced environments, balancing speed of execution with analytical rigor and governance.

Responsibilities

Strategic data acquisition & roadmap Define and own the strategic roadmap for third-party data, aligning with demand ans supply side partner objectives, marketing, risk, and product objectives. Proactively identify new data sources, bureaus, and providers that can enhance decisioning, market differentiation, network efficiency, and revenue generation. Help prioritize opportunities based on business impact, feasibility, and ROI
Data evaluation & value definition Lead data evaluation and proof-of-concept studies, including data profiling, coverage and stability assessment, and down-stream applicability of the said data. Drive off-line analytics and rapid predictive model development to quantify the incremental value of new data assets. Define clear frameworks to measure the economic value of data (e.g., lift in approval rates, Funnel efficiency, improved targeting, higher conversion or ARPU).
Business models & decision algorithms Partner with data science and product teams to define or refine business models and decision algorithms that incorporate third-party data. Translate insights into deployable decision rules, scorecards, and model features for batch and real-time decision systems. Ensure that new data is integrated with appropriate governance, monitoring, and performance tracking.
Vendor and bureau relationship management Serve as one of the critical points of contact for third-party data providers and bureaus, including contract discussions and ongoing performance reviews. Oversee bureau archiving strategies and ensure compliant, efficient use of archived data for back-testing, model development and analytics. Partner with legal, compliance, and procurement to help negotiate contracts, manage renewals, and optimize pricing and usage terms. Provide insights and support for platform level data purchasing algorithm development.
Experimentation & test platforms Use rapid experimentation platforms (e.g., Eppo, GrowthBook, Optimizely, VWO) to test the impact of new data-driven strategies in production. Design and interpret online tests that validate uplift from new data elements, segments, or decision rules. Build feedback loops that connect experimental results to long-term data acquisition and renewal decisions.
Decision systems & real-time data integration Collaborate with engineering and decision science to integrate third-party data into real-time decision systems and batch processes. Ensure SLAs, latency, and reliability of external data feeds meet business objectives. Help define monitoring and alerting for data quality, coverage drift, and vendor performance.
Business partnership & revenue opportunities Support business initiatives such as sizing, forecasting, and scenario analysis that depend on third-party data. Identify and articulate revenue opportunities enabled by new data (e.g., new products, expanded eligibility, improved pricing, better targeting or market differentiation). Present insights and recommendations to senior leadership, including tradeoffs between cost, investment, and revenue.
Leadership & mentoring Manage and mentor junior data scientists and analysts, providing guidance on analytics, modeling, experimentation, and stakeholder communication. Champion best practices in data evaluation, documentation, and experimentation across the broader analytics community.