Computer Science Marketing Jobs in Massachusetts

We’re hiring a Senior Data Scientist to lead a workstream within the Unified Measurement Engine (UME) team — owning end‑to‑end delivery as a senior individual contributor, setting technical direction, and mentoring peers. UME is building an industry‑leading measurement stack that integrates Marketing Mix Modeling (MMM), incrementality testing, and agile attribution to quantify the impact of marketing across owned, paid, and earned channels at enterprise scale.

You’ll own multiple concurrent projects across measurement methodology, large‑scale experimentation, and analytics product delivery — framing the business question, designing the approach, building the solution, and presenting findings to senior stakeholders (Lead Director, Executive Director, AVP, and VP+). You’ll run experiments touching 90M+ customers and hundreds of millions in media spend, co‑build alongside an industry‑leading measurement agency and vendor partners, and translate measurement insights into business strategy through regular recommendation sessions with VP‑and‑above audiences. You’ll set technical direction for your workstream, mentor junior data scientists, and tackle open research problems alongside a team of statisticians and builders — universal control design for owned media, brand impact measurement for paid media, media mix saturation (“how high is high”), cross‑channel measurement integration across digital and physical experiences, and meta‑learnings across studies.

• 3+ years of data science experience, with at least 2 years in marketing measurement, causal inference, or large‑scale experimentation
• Track record of analytical work that changed business decisions — not just answered questions
• Production‑grade Python and advanced SQL; proficiency with PySpark, Databricks, Snowflake, or equivalent distributed computing platforms
• Strong fundamentals in causal inference, experiment design, time‑series modeling, and Bayesian methods — with the judgment to pick the right tool for each problem
• Hands‑on experience with at least one of: MMM, incrementality testing, multi‑touch attribution, or geo‑experimentation
• Familiarity with the model lifecycle: training, validation, deployment, monitoring, and drift detection
• Ability to explain a model’s assumptions and limits to a non‑technical executive in three sentences
• Experience leading workstreams, mentoring peers, and partnering with senior stakeholders (Lead Director and above)

• Experience of leading advanced analytical and AI‑driven approaches (e.g., predictive modeling, machine learning, optimization, forecasting, and emerging AI applications) to address high‑impact business challenges.
• Experience as a technical lead or squad lead on a measurement, marketing science, or experimentation team
• Familiarity with performance and brand marketing metrics (ROAS, iROAS, lift, reach/frequency, brand equity)
• Experience working with measurement vendors or co‑building with external agencies
• Exposure to owned, paid and earned marketing data ecosystems (CRM, ad platforms etc.)
• Experience shipping analytical results into actionable recommendations to stakeholders

• Master’s or PhD in Statistics, Economics, Computer Science, Marketing Science, Operations Research, or related field strongly preferred.

40

Full time

The typical pay range for this role is:

$111,240.00 - $222,480.00

This pay range represents the base hourly rate or base annual full‑time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short‑term incentive program in addition to the base pay range listed above.

This full‑time position is eligible for a comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families. The benefits for this position include medical, dental, and vision coverage, paid time off, retirement savings options, wellness programs, and other resources, based on eligibility.

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.