Data Scientist

About the company

The company is building the world's most advanced marketing intelligence platform, providing top eCommerce brands a unified view of their business data through powerful attribution modeling and customizable dashboards. Our technology helps customers accurately track ad spend, understand the full customer journey, and drive profitable growth. Machine learning has been at the heart of the company since day one: our full suite of measurement, spanning multi-touch attribution, MMM+, and incrementality, is built on it, along with laser-accurate first-party data. Now we're taking that foundation further, using AI to help brands operationalize their data and turn the company insights into automated decisions.

We're experiencing rapid growth, have strong product-market fit, and are looking for the right people to help us scale. This is a rare chance to make a meaningful impact at a fast-moving, high-growth company. At the company, you'll join a team of driven, collaborative, and talented individuals who value personal growth and excellence. We'd love for you to be part of our journey.

We're a remote-friendly company with physical offices in San Francisco and Los Angeles.

About the Role

We are seeking a Data Scientist as a foundational member of our new "Applied Measurement" team.  In this role, you will help scale the company's incrementality and measurement products directly with customers, to help customers answer some of their most important marketing measurement questions.  You’ll work at the intersection of data science, causal inference, predictive modeling, and customer problems, contributing across the company’s measurement products.  This can include experimentation and incrementality products, Marketing Mix Modeling (MMM), and other predictive or machine learning products.

This is an applied Data Science role with direct exposure to real-world customer problems.  You’ll work closely with experienced Data Scientists and cross-functional partners across Media Strategy, Customer Success, Product, and Engineering.  As you develop deeper product and methodological expertise, you’ll have opportunities to contribute to new methodology, tooling, and scalable measurement capabilities.  You will also act as a trusted technical partner to clients: explaining statistical methodology, diagnosing measurement issues in their specific account, and clearly communicating experimentation results to drive actionable recommendations.

This role emphasizes customer partnership and applied communication as much as statistical methodology and production rigor.  The ideal candidate combines strong statistical foundations with a service-oriented mindset, and is comfortable moving between modeling, software development, and direct customer conversations.

Your Impact

• Partner with customers and internal teams to understand important marketing measurement questions and translate them into data science problems.

• Work with real-world customer data to ensure it is reliable and appropriate for modeling and measurement.

• Analyze model and experiment results, investigate unexpected outcomes, and identify potential data, modeling, or measurement issues.

• Translate complex statistical and modeling results into clear insights and actionable recommendations.

• Partner with Senior Data Scientists on more complex methodological and modeling problems. Collaborate with cross-functional peers to support clients with the practical application.

• Identify recurring challenges and opportunities to improve our models, diagnostics, tooling, and processes.

• Build reusable analysis and diagnostic tools that make measurement more reliable and scalable.

• As you grow in the role, contribute to the development of new methodologies, models, and production measurement capabilities.

What You Bring

• Bachelor's degree (MS preferred) in Computer Science, Statistics, Mathematics, Engineering, or another highly quantitative field.

• 2+ years of experience building and deploying data science, machine learning, or AI systems in production, ideally including direct client- or customer-facing work.

• Strong foundation in statistics, machine learning, experimentation, and causal inference, with genuine enthusiasm for explaining these methods to non-technical audiences.

• Excellent verbal and written communication skills—comfortable leading a customer conversation, explaining a modeling tradeoff to a non-technical stakeholder, and writing up findings clearly.

• Strong coding and debugging skills, with the ability to write production-quality code and diagnose issues across the full stack, including source data, pipelines, model logic, and customer-facing outputs.

• A service-oriented mindset: energized by direct, hands-on customer problem-solving, not only methodology for its own sake.

• Comfortable working in a fast-paced startup environment and driving projects from concept to production with a high degree of autonomy.

• Growth mindset, intellectual curiosity, and a willingness to learn new domains, customer verticals, and measurement methodologies.

• Strong preference for candidates with a robust statistical background and prior experience in digital marketing or eCommerce analytics.

Base Salary Range

$130,000 — $160,000 USD

Actual compensation may vary based on experience, skills, and location.

In addition to your base salary, we offer an equity package, comprehensive healthcare benefits (medical, dental, and vision), and a 401(k) plan. Our team enjoys a flexible PTO policy, 12 company-paid holidays, and 12 weeks of paid parental leave. We also provide a $500 work-from-home stipend to support your remote setup.

Interview Process

The interview process varies by role but typically begins with a 30-minute interview with the company recruiter, followed by a video interview with the hiring manager. Next, candidates complete a role-specific video interview followed by video or onsite interviews with several team members. The final step is a video interview with our CEO/Co-founder. The entire interview process is usually 5-7 interviews total and requires around 5-8 hours of your time.

We accept applications on an ongoing basis.