Sr. Director, Data Science & Experimentation

Reposted 10 Hours Ago
Be an Early Applicant
Hiring Remotely in United States of America
Remote
180K-392K Annually
Senior level
AdTech • Digital Media • Information Technology • Other
The Role
Lead and scale a data science and experimentation organization for Growth & Media. Own experimentation platforms and causal inference, build predictive and audience models, architect data pipelines and model-serving infrastructure, embed ML into marketing workflows, increase testing velocity, and present actionable findings to senior leadership to optimize acquisition, engagement, and budget allocation.
Summary Generated by Built In
Yahoo serves as a trusted guide for hundreds of millions of people globally, helping them achieve their goals online through our portfolio of iconic products. For advertisers, Yahoo Advertising offers omnichannel solutions and powerful data to engage with our brands and deliver results.

A Little About Us

Our team is focused on accelerating growth across Yahoo's consumer portfolio by bringing together performance marketing, media, data science, and experimentation. We build the measurement, experimentation, and technical capabilities that help drive customer acquisition, engagement, and long-term growth.

Position Overview

As the Sr. Director of Data Science & Experimentation, you'll build and lead the quantitative backbone that powers marketing decisions across Yahoo's Growth & Media organization. From experimentation and causal inference to predictive modeling and real-time audience signals, your team will help shape how we measure performance, optimize investment decisions, and improve customer acquisition and engagement.

This role is for a builder who is equally comfortable designing the statistical architecture of a major experiment and translating complex findings into clear recommendations for senior business leaders. You'll partner closely with Performance Marketing, Media Planning, and technical product leadership to integrate machine learning models, experimentation capabilities, and intelligent automation into Yahoo's growth marketing infrastructure.

What You'll Do

  • Own the experimentation platform and methodology for the Growth & Media team, including A/B testing, incrementality studies, geo holdouts, matched market tests, and multi-armed bandit frameworks that improve decision speed.

  • Build and lead a team of data scientists and analysts focused on growth measurement, marketing attribution, audience modeling, customer lifetime value prediction, and forecasting.

  • Develop causal inference frameworks that measure the true incremental impact of paid, organic, and owned marketing programs, moving beyond last-click attribution to more rigorous measurement.

  • Architect and oversee the data pipelines, feature stores, and model-serving infrastructure that power real-time campaign optimization and audience targeting.

  • Design and deploy predictive models, including propensity, customer lifetime value, churn, recommendation, and lookalike audience models that inform budget allocation, targeting, and retention strategies across channels.

  • Work closely with technical product leadership on agentic growth tooling to embed machine learning signals and model outputs into autonomous marketing workflows, enabling agents to act on high-quality data.

  • Establish and scale the team's experimentation culture by increasing testing velocity, improving statistical rigor, and building tools that make experimentation a core part of how the team operates.

  • Present complex analytical findings and strategic recommendations in a clear, actionable way for senior leadership.

  • Evaluate emerging technologies, including AI-powered capabilities, where they can improve marketing performance, operational efficiency, or decision-making.

What You Bring

  • 12+ years in data science or applied machine learning, with 4+ years building and leading high-performing data science or analytics teams.

  • Deep expertise in causal inference and experimentation design, including A/B testing, difference-in-differences, holdout methodologies, and Bayesian experimental frameworks.

  • Strong machine learning background with experience building, validating, and deploying propensity models, forecasting models, recommendation systems, or audience models in production.

  • Proficiency in Python and SQL, with experience using distributed computing frameworks such as Spark, BigQuery, Databricks, or equivalent technologies.

  • Experience building or meaningfully scaling an experimentation platform within a consumer internet or marketing-intensive organization.

  • Proven ability to translate complex model outputs and statistical findings into clear business recommendations for technical and non-technical audiences.

  • Track record of embedding data science into day-to-day marketing and product decisions through close partnership with cross-functional teams.

Preferred Qualifications

  • Experience with marketing mix modeling (MMM) and multi-touch attribution (MTA) at scale.

  • Familiarity with agentic AI systems and how machine learning signals support autonomous, real-time decision making in marketing workflows.

  • Advanced degree (MS or PhD) in Statistics, Computer Science, Applied Mathematics, or a related quantitative field.

What Success Looks Like

Success in this role means establishing scalable experimentation and measurement capabilities that help teams make smarter marketing decisions. You'll improve how the organization measures marketing effectiveness, increase experimentation velocity, and embed machine learning into marketing workflows in ways that create meaningful business impact.

#LI-BD2

The material job duties and responsibilities of this role include those listed above as well as adhering to Yahoo policies; exercising sound judgment; working effectively, safely and inclusively with others; exhibiting trustworthiness and meeting expectations; and safeguarding business operations and brand integrity.

At Yahoo, we offer flexible hybrid work options that our employees love! While most roles don’t require regular office attendance, you may occasionally be asked to attend in-person events or team sessions. You’ll always get notice to make arrangements. Your recruiter will let you know if a specific job requires regular attendance at a Yahoo office or facility. If you have any questions about how this applies to the role, just ask the recruiter!

Yahoo is proud to be an equal opportunity workplace. All qualified applicants will receive consideration for employment without regard to, and will not be discriminated against based on age, race, gender, color, religion, national origin, sexual orientation, gender identity, veteran status, disability or any other protected category. Yahoo will consider for employment qualified applicants with criminal histories in a manner consistent with applicable law. Yahoo is dedicated to providing an accessible environment for all candidates during the application process and for employees during their employment. If you need accessibility assistance and/or a reasonable accommodation due to a disability, please submit a request via the Accommodation Request Form (www.yahooinc.com/careers/contact-us.html) or call +1.866.772.3182. Requests and calls received for non-disability related issues, such as following up on an application, will not receive a response.

We believe that a diverse and inclusive workplace strengthens Yahoo and deepens our relationships. When you support everyone to be their best selves, they spark discovery, innovation and creativity. Among other efforts, our 11 employee resource groups (ERGs) enhance a culture of belonging with programs, events and fellowship that help educate, support and create a workplace where all feel welcome.

The compensation for this position ranges from $180,310.00 - $392,430.00/yr and will vary depending on factors such as your location, skills and experience.The compensation package may also include incentive compensation opportunities in the form of discretionary annual bonus or commissions, in addition to equity incentives. Our comprehensive benefits include healthcare, a great 401k, backup childcare, education stipends and much (much) more.

Currently work for Yahoo? Please apply on our internal career site.

Skills Required

  • 12+ years in data science or applied machine learning with 4+ years building and leading data science or analytics teams
  • Deep expertise in causal inference and experimentation design (A/B testing, difference-in-differences, holdouts, Bayesian frameworks)
  • Experience building, validating, and deploying propensity, forecasting, recommendation, churn, or audience models in production
  • Proficiency in Python and SQL
  • Experience with distributed computing frameworks such as Spark, BigQuery, or Databricks
  • Experience building or meaningfully scaling an experimentation platform within a consumer internet or marketing-intensive organization
  • Proven ability to translate complex statistical and model outputs into clear business recommendations for technical and non-technical audiences
  • Track record of embedding data science into day-to-day marketing and product decisions through cross-functional partnership
  • Experience with marketing mix modeling (MMM) and multi-touch attribution (MTA) at scale
  • Familiarity with agentic AI systems and autonomous, real-time ML-driven marketing workflows
  • Advanced degree (MS or PhD) in Statistics, Computer Science, Applied Mathematics, or related quantitative field
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The Company
HQ: Sunnyvale, CA
10,001 Employees

What We Do

Yahoo is a global media and tech company that connects people to their passions. We reach nearly 900 million people around the world, bringing them closer to what they love—from finance and sports, to shopping, gaming and news—with the trusted products, content and tech that fuel their day. For partners, we provide a full-stack platform for businesses to amplify growth and drive more meaningful connections across advertising, search and media.

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