Staff Data Scientist, Product
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Summary
A hands-on technical lead for a small data science team building Fetch's off-platform data business: predictive audience models, relevance/ranking, and ad measurement systems grounded in causal inference. Core tooling is Python, SQL, Snowflake, and dbt, with work carried from prototype to production alongside engineering.
Meet Fetch AI & Data
AI & Data at Fetch sit at the center of how we understand our business, make decisions, and build intelligent products. The organization operates as an integrated AI & data ecosystem, spanning multiple disciplines, including data engineering, analytics engineering, machine learning, experimentation, and data platforms, all working together to turn data into durable business and customer impact.
Teams operate in complex problem spaces where requirements evolve, tradeoffs are constant, and the right answer is rarely obvious. Success depends on strong technical judgment, comfort with ambiguity, and the ability to gather context and make informed decisions while balancing quality, performance, scalability, and responsible use.
Practitioners across this org contribute hands-on to production systems, analytical foundations, and intelligent features. You will collaborate closely with product, platform, and engineering partners, help shape standards and best practices, and ensure our AI and data capabilities scale reliably as Fetch grows.
About the Role
Fetch’s off-platform data business monetizes our data beyond the app through audience segments, measurement capabilities, and data feeds. We are seeking a Staff Data Scientist to build the foundations of this business and accelerate its growth, serving as technical lead for a small team of data scientists while remaining hands-on in building the models and systems behind our data products.
You’ll set the technical direction across audiences, measurement, and data feeds, and personally architect and build the models and systems behind them, from early prototypes through scalable production use. On the audience side, you’ll build predictive models that extend Fetch’s reach well beyond our own user base, shape the relevance and ranking approaches that match the right audiences to each advertiser’s goals, and apply those capabilities to in-product work as well. On the measurement side, you’ll own the frameworks that turn campaign data into trusted proof of sales impact, using causal inference to separate true advertising effects from noise.
You’ll also set the quality bar for your team through hands-on mentorship and rigorous reviews, champion our methodology with customers, partners, and industry leaders, and align senior leaders around clear, decisive recommendations. You’ll build strong partnerships across product, engineering, and Go-to-Market teams to help establish Fetch’s approach as a trusted market standard.
This is a full-time role that can be held from one of our US offices or remotely in the United States.
What you’ll do at Fetch
- Lead a small team of data scientists as technical lead, owning the quality and delivery of the team's work.
- Set the technical direction and roadmap across audiences, measurement, and data feeds, partnering with product and engineering on the design, quality, and coverage of the data delivered to partners.
- Architect and build the models and systems behind our data products.
- Develop data scientists in causal inference, predictive modeling, and clear communication.
- Build predictive models that identify likely buyers and extend audiences beyond Fetch's user base.
- Shape relevance and ranking approaches that match the right audiences to advertiser goals.
- Define how audience quality is evaluated and articulate what differentiates Fetch audiences in a crowded market.
- Extend these models to in-product use cases, such as acquiring high-value users for Fetch.
- Own the measurement frameworks that connect ad exposure to verified conversions using Fetch data, and turn one-off analyses into repeatable, scalable products.
- Drive the application of causal inference and experimental design to establish whether advertising drove outcomes.
- Champion our methodology with customers, partners, and industry leaders, anticipating the challenges they will raise.
- Establish our approach as a trusted market standard through clear documentation and evangelism.
- Align senior leaders around clear, decisive recommendations on strategy and tradeoffs.
- Develop strong partnerships across product, engineering, and Go-to-Market teams, including sales and business development.
- Carry work from prototype to production alongside ML engineering, data engineering, and platform teams.
- Spot gaps others haven't, build alignment across stakeholders, and sustain momentum on long-running initiatives.
In your Toolbox
- 8+ years of total experience in data science or applied statistics, including 3+ years of industry experience building ads platform capabilities, such as audience products or measurement systems.
- Strong statistical foundation, with deep expertise in causal inference and advertising measurement.
- Hands-on experience building and architecting predictive modeling systems for advertising as well as relevance and ranking systems.
- Experience building systems that run beyond a prototype, with the ability to partner with engineering to take them into production.
- Experience leading or mentoring other data scientists, including setting technical direction and reviewing the quality of their work.
- Experience leveraging modern analytics tooling such as Python, SQL, Snowflake, and dbt.
- A clear track record of influencing senior leadership and partnering with product and engineering stakeholders.
- Clear and decisive written and verbal communication, including the ability to explain complex methodology to non-technical audiences.
- Demonstrated initiative in identifying problems others haven’t and driving them to resolution across teams.
- Demonstrated ability to evaluate AI tools critically and apply them where they meaningfully improve results.
- Bachelor’s degree in a quantitative field.
Nice to Haves
- Advanced degree in a quantitative discipline.
- Experience with off-platform and programmatic advertising or identity.
- Experience defending measurement or audience methodology in conversations with external customers or industry partners.
- Experience partnering with GTM, sales, or business development teams.
- Experience with retail or CPG purchase data.
Compensation: At Fetch, we offer competitive compensation packages including base, equity, and benefits to the exceptional folks we hire. Discover our benefits and how our employees live rewarded at .
