Principal Data Scientist; _

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Affinity Solutions (Affinity) is the leading consumer purchase insights company. We provide a complete view of U.S. and U.K. consumer spending, across and between brands, via exclusive access to fully permissioned data from over 100 million consumers. Our proprietary AI technology, Comet™, transforms these purchase signals into actionable insights for business and marketing leaders to drive optimal outcomes and build lasting customer relationships.

Visit  to discover how we’re shaping the future of consumer purchase insights.

The Data Science team at Affinity Solutions builds the statistical and machine learning capabilities that turn raw credit card transactions into an AI-ready source of truth for consumer spending behavior — the models that resolve messy transaction strings into canonical brands and categories, the predictive models that turn spend history into forward-looking signals, and the methodology that measures campaign effects defensibly.

Increasingly this work will be consumed by models and agents rather than by analysts, which raises the bar on correctness, robustness and privacy.

In this role, you will serve as the technical lead for the Quantitative Intelligence area, spanning three core disciplines — predictive modeling, statistical weighting and paneling methodology, and campaign measurement. The goal of this group is to turn Affinity’s consumer spend data into predictive and statistical intelligence — models and signals that are served as first-class, governed capabilities to our customers, our products, and the AI agents that will increasingly consume our data.

Example problems include predicting a customer’s future spend at a merchant, long-term brand and category spend forecasting, modeling ticker performance, propensity and churn models, privacy-safe behavioral embeddings, reusable feature and training-set generation for customer-built models, pseudo-randomized campaign measurement, and evaluation methodologies and frameworks that ensure these models work well.

You will work hands-on alongside this team while also setting its technical roadmap, with a path to formally managing this group as it grows.

• Set the technical roadmap and standards across predictive modeling, statistical weighting and paneling, and campaign measurement, so the three disciplines share one methodological foundation rather than diverging practices.
• Serve as tech lead for a team of scientists and engineers spanning these three areas.
• Own and advance the paneling and weighting framework that creates cost-optimized panels — stable subsets of data that reduce costs while balancing and normalizing the data to maintain representativeness and statistical quality.
• Contribute to our campaign measurement methodology — synthetic control creation, identity resolution, metric computation — and ensure it meets the reproducibility and audit standards the architecture requires.
• Guide the R&D roadmap for predictive models over the full transaction history — merchant-level spend prediction, category and brand forecasting, propensity and churn scores, and brand/ticker performance models, including model evaluation, feature/label pipelines, and embeddings work that supports them.
• Apply and champion privacy-preserving modeling techniques — aggregation thresholds, perturbation-aware modeling, and differentially private training — across all three disciplines, and ensure models operate correctly within cleanroom constraints.
• Drive…