VP of Data Product

Responsibilities

• Define the multi-year portfolio roadmap for Attain’s underlying data asset, marketing science feeds, and extrapolated and predicted data products.
• Lead Data Product PMs and the execution function responsible for feed delivery, pipeline architecture, QA, match tests, and vendor management.
• Partner with data science to translate client and market needs into modeling priorities and convert model outputs into shippable, explainable data products.
• Own productization of incrementality signals, propensity and ad responsiveness scores, brand switching and loyalty metrics, and brand choice models into licensed feeds and scores.
• Apply AI methods to data extrapolation, prediction, and scaling.
• Serve internal measurement, insights, audience, and activation teams as product customers.
• Champion privacy, consumer permissions, consent, and regulatory compliance.
• Drive data licensing, pricing strategy, client adoption, revenue growth, retention, and expansion.

Requirements

• Extensive experience in data products, marketing science, ad measurement, or media analytics.
• At least 3 years leading teams, including experience managing senior product leaders and technical execution functions.
• Experience owning a commercially licensed data product such as feeds, scores, APIs, or datasets with revenue and SLAs.
• Experience applying AI methods to data extrapolation or similar problems.
• Working fluency in marketing science and causal measurement, including incrementality, selection bias, and baseline evaluation.
• Experience directing data scientists and evaluating modeled outputs.
• Deep understanding of transaction-level data products, merchant and UPC/SKU structures, taxonomy, identity resolution, match rates, and panel-to-population projection.
• Understanding of audience activation, measurement, planning, clean room workflows, and the identity landscape.
• Track record converting data assets into licensing revenue and business outcomes.
• Executive-level communication skills across leadership, client data science, and engineering audiences.
• Experience with consumer-permissioned, panel, or purchase graph data and related privacy and compliance requirements.
• Familiarity with retail media networks, CTV measurement, unified IDs, and walled-garden constraints.
• Exposure to discrete choice, Dirichlet/NBD loyalty modeling, Markov switching, MMM, attribution, and causal machine learning.
• Experience with data licensing, pricing, and clean room delivery platforms such as Snowflake, LiveRamp, or Databricks.
• Ad tech startup or scale-up experience.

Nice-to-haves

• Hands-on modeling experience.
• Experience working with PhD-level scientists and sophisticated client data science teams.
• Experience productizing methodology-driven marketing science outputs.

Success Measures

• Growth in data product revenue, adoption, and retention.
• Validated methodologies for derived and predicted fields that withstand advertiser, agency, and academic scrutiny.
• A scaled data product organization with reliable delivery and a roadmap-aligned data science function.
• Increased use of canonical feeds and improved internal customer satisfaction.
• Recognition of Attain’s data as a credible standard for consumer-permissioned purchase data.