About this role
The team builds a commerce partnership marketing platform that enables businesses to discover, manage, and scale partnerships across the entire customer journey. The Senior Data Scientist will lead modeling research across measurement initiatives such as attribution, identity resolution, and tracking quality, while also owning the pipelines supporting end-to-end measurement and incrementality testing.
Operating as a high-impact individual contributor in New York City, the person in this job will design experiments to quantify attribution lift, evaluate vendor solutions through structured proofs of concept, and bridge technical integrity with business strategy. An ideal candidate brings strong engineering rigor, deep experience in attribution and measurement, and the ability to translate complex technical tradeoffs into actionable narratives for leadership and cross-functional partners.
What you will do
- Analyze current measurement solutions to identify systemic weaknesses and develop next-generation approaches using machine learning and graph networks.
- Build and maintain robust testing environments, pipelines, and monitoring systems for model evaluation in partnership with data engineering.
- Design and execute incrementality experiments and A/B tests to verify the measurable business impact of algorithmic changes.
- Serve as the technical owner for third-party identity partner evaluations by designing structured proofs of concept to test vendor claims against real data.
- Translate complex technical findings and data-driven recommendations into clear narratives for product, engineering, and leadership stakeholders.
- Drive the technical measurement strategy for high-priority initiatives in collaboration with other internal teams.
What you need
- Bring 5 or more years of total experience with significant, hands-on expertise in data-driven research and development.
- Demonstrate a proven track record in designing incrementality experiments, A/B testing, and assessing the impact of new initiatives.
- Possess the ability to build production-grade pipelines with fluency in Python and SQL.
- Hold a Bachelor's degree in a quantitative field such as computer science, statistics, math, or engineering, with higher degrees preferred.
- Effectively articulate complex technical tradeoffs to stakeholders involved in build-versus-buy decisions.
Nice to have
- Familiarity with machine learning-based entity resolution approaches like blocking strategies, embedding-based similarity, and probabilistic matching.
- Experience with graph databases and graph analytics applied to identity or entity data.
- Deep understanding of multi-touch attribution and cross-channel measurement.
- Experience with device fingerprinting, cross-device identity, or cookie-less identity resolution approaches.
- Knowledge of privacy-preserving identity techniques such as differential privacy and clean rooms.
Benefits
- Medical, Dental, and Vision insurance
- Office-only catered lunch every Thursday, a healthy snack bar, and great coffee
- Flexible spending accounts and 401(k)
- Responsible PTO policy for flexible time off
- Mental health and wellness benefit including up to 12 fully covered therapy or coaching sessions per year
- Monthly gym reimbursement policy and Restricted Stock Units with a 3-year vesting schedule
Skills and tech stack
Questions candidates ask
What is the salary range for this role?
The salary range is $130,000 to $142,000 per year. Additional compensation includes eligibility for a Restricted Stock Unit grant and a variable annual bonus contingent on company performance.
Where is the position located?
The role is based in New York City.
What kind of experience is required for applicants?
Candidates must have 5 or more years of total experience with significant, hands-on expertise in data-driven research and development. A background in attribution, measurement, experiment design, and production-grade pipeline building in Python or SQL is also required.