Data Scientist

The Role

We are looking for a Data Scientist to sit at the center of Thrad's decision-making. Every day we serve millions of ad impressions across dozens of publishers and campaigns, and almost every meaningful question at the company (pricing, yield, publisher economics, advertiser performance, category expansion) is a data question. You will own answering them.

This is not a dashboards-on-request role. You will sit inside product and engineering, drive decisions through rigorous causal reasoning, and level up how the whole team thinks about metrics. Your work will directly shape what we build, what we price, and where we grow. You will work closely with our CTO, the founding engineering team, and the commercial team on both internal insight and client-facing reporting.

Core Tech Stack

• Data: ClickHouse for analytics and real-time metrics, PostgreSQL for transactional, Redis for caching

• Languages: SQL (heavy), Python, notebooks for exploration and production modeling alike

• Experimentation: in-house A/B testing against live traffic on our publisher network

• BI and reporting: the team's choice, shipped to both internal stakeholders and Fortune 500 clients

• Plus: whatever the problem demands. We pick tools that ship.

Example Projects

• Build and maintain the analytical infrastructure for ad performance: CTR, CPC, ROAS, CPM, fill rate, yield, across publishers, advertisers, and verticals.

• Design causal experiments on ad formats, bidding strategies, creative variations, and publisher configurations. Own them from hypothesis to conclusion.

• Partner with the CRO on pricing experiments, publisher revenue-share modeling, and advertiser performance reviews.

• Use statistical modeling to turn rich marketplace data into tools that directly shape product decisions: propensity models, yield curves, cohort analyses.

• Build self-serve dashboards so the rest of the team can answer their own questions against live metrics without a data bottleneck.

• Own the data model in ClickHouse and the reporting layer feeding both internal dashboards and client-facing performance reports.

• Help level up the whole team. Encourage data-driven decisions and a deep understanding of the metrics that drive the business forward.

What You Will Do

• Drive product and commercial decisions using data and causal reasoning, embedded directly in the engineering and go-to-market teams.

• Design, implement, and execute experiments against live traffic. Analyze results rigorously and kill or scale them fast.

• Move from a vague business question to a defensible number in a day.

• Build and maintain the dashboards and reports that both the team and our clients rely on.

• Collaborate directly with the CTO, co-founders, and commercial team to translate data into action, often within the same day.

• Contribute to system and schema decisions as we scale from millions to billions of daily ad impressions.

Who You Are

Must-haves

• 2 to 5 years in data science, analytics engineering, or quantitative analysis. Bonus if you have worked on marketplaces, ads, or other high-velocity data products.

• An advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related field, or equivalent experience shipping analytical work that drove real decisions.

• Strong SQL. You can write, optimize, and debug complex queries without reaching for a tool.

• Solid Python for modeling, analysis, and lightweight production work.

• Strong fundamentals in mathematical and statistical modeling. You know when to trust a number and when to distrust it.

• Comfort with experimentation end to end: A/B testing, causal inference, power analysis, sample size calculations, and honest reporting of negative results.

• Clear written and verbal communication. You can explain a causal finding to an engineer, a founder, and a Fortune 500 client in the same afternoon.

• Based in San Francisco or willing to relocate. This is an in-person role at our SF HQ.

Nice-to-haves

• Experience with ClickHouse or other column-oriented OLAP databases at scale.

• Background in ad tech, programmatic advertising, or two-sided marketplaces.

• Experience building client-facing dashboards or reporting products used by external customers.

• Familiarity with dbt, Metabase, Hex, or similar tools.

• Comfort reading production code to understand where data comes from and where it goes.

• A relentless focus on continuous learning and the ability to question the status quo when the numbers say you should.

Why Thrad

• First mover: We are defining a new category. Paid ads in AI is an inevitable market and we are building the infrastructure for it.

• Real traction: Fortune 500 clients, millions of daily impressions, and publisher partners across the AI web, all pre-seed.

• Rich data: A marketplace running at real scale from day one. Your models and experiments have immediate, measurable impact on revenue.

• Direct impact: Small founding team. Your insights shape pricing, product, and strategy the same week you surface them.

• Ownership: Meaningful equity in a company at the intersection of two massive markets: AI and ad tech.

• Craft: A team that cares about shipping quality, not just quantity.

How to Apply

Send your CV and a brief note on what excites you about building at the intersection of AI and advertising. If you have notebooks, write-ups, experiments, or dashboards you have built that you are proud of, include them. We read every application.