# VP of Data Science

**Company:** [Attain](https://hotfix.jobs/companies/attain)
**Location:** Chicago, IL, New York, NY, Redwood City, CA
**Role:** Data Science
**Experience:** 10+ years
**Skills:** Causal Inference, Incrementality, Attribution, Media Mix Modeling, Bayesian Methods, Experimental Design, Python, Machine Learning, Statistical Modeling, Cloud Data Stack, Consumer Data, Bias Correction
**Posted:** 2026-08-28

> Leads Attain’s data science methodology and team, owning defensible measurement, causal inference, attribution, and modeled consumer-data products. The role requires deep AdTech/MarTech expertise, strong statistical and Python skills, client-facing credibility, and at least 10 years of experience.

## Job Description

## Responsibilities
- Define and maintain standards for measuring impact, proving causality, and validating modeled data.
- Own methodology and modeling for census balancing, attribution, audience targeting, incrementality, and validation regimes.
- Establish and document consistent, defensible standards for attribution windows, touch-model methodology, and ROAS conventions.
- Represent Attain’s methodology to engineering, commercial, and external stakeholders.
- Translate advanced statistical methods into product decisions and business recommendations, while incorporating commercial needs into the scientific roadmap.
- Partner with Engineering and ML leadership on modeling infrastructure and standards without directly owning the infrastructure.
- Develop and lead a team of data scientists.
- Manage engagements with external consultants and domain specialists.

## Requirements
- 10+ years of data science experience in AdTech or MarTech, including 4+ years leading a team.
- Senior-level ownership of measurement science or methodology in AdTech, MarTech, or a data-driven consumer platform.
- Deep expertise in causal inference, incrementality, attribution, and media mix modeling.
- Strong statistical foundation in Bayesian methods and experimental design.
- Hands-on experience with large-scale consumer datasets, including transaction, purchase, panel, identity, modeled, or synthetic data.
- Experience addressing imputation, matching, coverage gaps, and bias correction.
- Experience presenting and defending modeling approaches to clients, partners, or regulators.
- Strong Python and modern machine learning/statistical tooling skills.
- Comfort operating on a cloud data stack.
- Excellent communication and presentation skills across technical, commercial, and executive audiences.

## Nice-to-haves
- Advanced degree such as an MS, PhD, or MBA in economics, statistics, or a related quantitative field.
- Experience building and scaling a data science team.
- Experience with panel-based or modeled/synthetic consumer data.

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