Head of Residual Strategy

Hearst•Lawrenceville, GA

20h•Onsite

About The Position

Due to continued growth, and the successful introduction and adoption of Black Book’s industry-leading data and analytics products and services, Black Book, one of the most recognized brands in the automotive and automotive finance industries, is expanding its Senior Management Team with the addition of a new executive leadership role. This strategic investment reflects the company’s commitment to accelerating future growth, driving innovation, and further strengthening its position as a trusted leader across the automotive ecosystem. As Black Book continues to invest significantly in technology, data intelligence, and market expansion initiatives, this new role will play a critical part in helping shape and execute the company’s long-term business strategy. Position Summary Based in our suburban Atlanta corporate office and reporting to the President, the Head of Residual Strategy will lead our residual value modeling and predictive valuation capability across the U.S. and Canada. This is a high-impact leadership role responsible for one of the core economic engines of the business—residual value forecasting and analytics. You will own the strategy, modeling direction, and performance of residual outputs, ensuring they are accurate, stable, explainable, and trusted by the market. Operating at the intersection of data science, domain expertise, and product, this role translates complex modeling capabilities into customer value, product innovation, and revenue growth while serving as a key external voice for Black Book, representing our residual strategy and market perspective with clients, partners, and industry stakeholders while helping strengthen Black Book’s position as a trusted authority in residual value forecasting and risk analytics.

Requirements

15+ years in auto finance, residual modeling, forecasting, and/or related analytics domains
Bachelors degree in Data Science or related field such as Mathematics, Statistics or computer science.
Masters or PhD strongly preferred
Deep understanding of leasing economics, residual risk, and ABS/securitization markets
Experience with statistical modeling, machine learning approaches, and AI adoption
Experience working directly with captives, lenders, and institutional investors
Ability to bridge technical modeling and business strategy
Strong understanding of model behavior, limitations, and explainability
Ability to communicate complex outputs clearly to technical and business audiences
High credibility in customer-facing environments

Nice To Haves

Experience building or scaling data products
Exposure to API-based delivery and analytics platforms
Experience working with production AI/ML systems

Responsibilities

Own residual value forecasts across new and used vehicles
Define and evolve modeling approaches including mileage, trims, volatility, segmentation, and model-year transitions
Ensure outputs are accurate, stable, explainable, defensible, and aligned to customer and market needs
Support use cases across captives, lenders, ABS/securitization, insurance, and fleet analytics
Expand residual capabilities and enable new analytics opportunities
Define modeling objectives and success criteria around accuracy, stability, and explainability
Partner with Data Science to guide development approaches, feature design, and target definitions
Ensure models adhere to established QA, validation, and documentation standards
Establish scalable lifecycle processes across development, validation, release, monitoring, and iteration
Manage exception handling, volatility controls, and release readiness
Ensure strong documentation, terminology consistency, and knowledge transfer
Serve as a trusted advisor to captives, lenders, institutional investors, fleet organizations, and insurance carriers
Lead resolution of customer escalations and methodology challenges
Support strategic sales conversations, portfolio analysis, and risk-related engagements
Clearly communicate model behavior, market shifts, and residual trends
Partner with Product to translate residual capabilities into customer-facing solutions
Influence roadmap prioritization and monetizable analytics opportunities
Support go-to-market efforts through messaging, use case development, and deal support
Drive scalable product innovation and revenue-generating opportunities
Define Black Book’s perspective on residual risk, market volatility, and portfolio performance
Lead and contribute to market outlooks, residual value reports, and conference presentations
Strengthen Black Book’s position as a trusted authority in residual analytics and forecasting
Lead a dedicated Residual Data Science team and Residual Analyst function
Partner across Data Science, Product, Data & Market Intelligence, BI, Sales, and Marketing
Drive alignment across teams to ensure clear ownership, efficient execution, and consistent outputs