Data Scientist, Marketing

Our vision at Descript is to build the next-generation platform for fast and easy creation of audio and video content. We are trusted by some of the world's top podcasters and influencers, as well as businesses like BBC, ESPN, HubSpot, Shopify, and The Washington Post for communicating via video. We've raised $100M from leading investors such as the OpenAI Startup fund, Andreessen Horowitz, Redpoint Ventures, and Spark Capital.

We are looking for a strategic and hands-on Marketing Data Scientist to join our Growth team. You’ll partner closely with Performance marketing team to architect our measurement framework, optimize performance across full-funnel marketing, and enable smarter business decisions through data.

This is a pivotal role for scaling Descript's marketing engine across both B2C product-led and B2B sales-led growth motions. You'll pioneer the use of AI-enhanced analytics tools that automate strategic decision-making processes and deliver predictive insights at scale.

This role can be remote in the US or based in the SF Bay Area.

What You’ll Do

Define and Evolve Marketing Measurement

• Develop channel specific CAC targets accounting for audience intent and funnel stage
• Iterate and improve attribution models, while navigating platform-reported limitations and first-party data availability
• Drive incrementality measurement, partnering with the performance marketing team to design and run in-house conversion lift experiments
• Design and build AI-powered tools that automate routine marketing analyses and surface actionable insights

Build Core Dashboards & Reporting

• Own the creation and ongoing refinement of marketing dashboards
• Ensure clear, automated, and actionable reporting on acquisition, retention, and monetization

Lead Modeling & Forecasting Initiatives

• Create models to score leads based on their likelihood to convert, helping sales and marketing teams prioritize high-value prospects
• Build models to forecast campaign performance and support monthly budget allocation
• Develop recommendation systems that leverage user behavior data to suggest optimal channel mix and budget allocation

Be a Strategic Partner

• Collaborate with Marketing, Sales, Product, and Analytics Engineering to ensure data quality, interpretability, and usability.
• Champion high standards for experimentation, measurement, and statistical rigor across the org.
• Proactively identify trends, patterns, and opportunities through data to improve day-to-day operations and drive user acquisition, activation, and retention.

What You Bring

• Extreme ownership and resourcefulness to get things done.
• Deep understanding of ads platforms (Meta, Google, Microsoft), data enrichment, and reverse ETL process through a CDP such as Segment or Census.
• Strong working knowledge of incrementality testing, randomized controlled experiments and quasi-experiments.
• Experience with building in-house attribution models
• Proven success working with both product-led growth funnels and sales-led GTM motions.
• Experience with AI tools and frameworks for marketing analytics and optimization
• Familiarity with LLMs and how they can be leveraged to enhance marketing insights
• Understanding of how to build and deploy AI-powered prediction models for user behavior and conversion
• Bachelor's or Master's degree in a relevant field (e.g. computer science, mathematics, statistics, etc).
• 5+ years of experience in a data scientist or related role.
• Proficient in SQL and at least one programming language such as Python or R.

At our current size and stage, we embrace a flat organizational structure and value the expertise and contributions of every team member. As such, we have a unified job title for our engineering roles where everyone, including those with Staff-level scope, is considered a Data Scientist. While titles may not change, we are actively seeking a senior and above Data Scientist to join our team.

The base salary range for this role is $144,000- $192,000/year. Final offer amounts will carefully consider multiple factors, including prior experience, expertise, location, and may vary from the amount above.