Why This Job is Featured on The SaaS Jobs
In a SaaS landscape where product-led growth and data-informed GTM are increasingly intertwined, this Data Scientist role stands out for its proximity to the full customer funnel. Clay positions itself as a platform used by go-to-market teams to operationalise data, experimentation, and automation—an environment where analytics is not a back-office function but part of how the product and revenue engine evolve.
For a SaaS career, the long-term value here is the chance to build judgment across the metrics that matter: activation, retention, monetisation, and the causal impact of product and GTM changes. The remit spans both insight generation and data enablement, which mirrors how many modern SaaS companies expect data scientists to operate—combining experimentation design, stakeholder communication, and foundational work that makes analysis repeatable and trusted.
This role is best suited to someone who prefers ownership over narrow task execution and is comfortable translating ambiguous questions into measurable hypotheses. It will likely fit a practitioner who enjoys partnering with non-technical teams while still staying close to the data stack, and who wants a seat near decision-making rather than a purely model-building track.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
About Clay
Clay is a creative tool for growth. Our mission is to help businesses grow — without huge investments in tooling or manual labor. We’re already helping over 100,000 people grow their business with Clay. From local pizza shops to enterprises like Anthropic and Notion, our tool lets you instantly translate any idea that you have for growing your company into reality.
We believe that modern GTM teams win by finding GTM alpha — a unique competitive edge powered by data, experimentation, and automation. Clay is the platform they use to uncover hidden signals, build custom plays, and launch faster than their competitors. We’re looking for sharp, low-ego people to help teams find their GTM alpha.
Why is Clay the best place to work?
Customers love the product (100K+ users and growing)
We’re growing a lot (6x YoY last year, and 10x YoY the two years before that)
Incredible culture (our customers keep applying to work here)
Well-resourced - We raised a $100M Series C in 2025 at a $3.1B valuation and are backed by world-class investors like Capital G (Google), Sequoia and Meritech
Read more about why people love working at Clay here and explore our wall of love to learn more about the product.
Data Science @ Clay
We’re looking for a data science "Olympian" to own full-funnel insights—from shaping our data infrastructure and asking the right questions to running experiments and delivering sharp analyses. You'll play a pivotal role in driving strategic decisions and building a data-driven culture. Our data stack is best in class (we use Snowflake, dbt, Dagster, Hex, Sigma, Eppo, and Census)
Impact You'll Have
Drive strategic insights: Own the full-funnel insight process, transforming data into actionable recommendations for go-to-market and product
Deliver clarity: Translate complex data findings into simple, actionable insights that resonate with both technical and non-technical stakeholders
Set up data infrastructure: Contribute to building and scaling our data transformation and orchestration capabilities, ensuring accurate and timely data delivery
Empower self-serve analytics: Develop a robust self-serve analytics platform that empowers all teams to access and leverage data effectively
Champion a data-driven culture: Establish best practices that encourage non-data teams to use insights effectively
Experiment: Design and set up experiments that test hypotheses and measure impact, driving continuous improvement in processes and products
What You'll Bring
4+ year experience
Expert in SQL and Python or R
Robust understanding of statistical and machine learning methods
Experience with data transformation tools (dbt) and data orchestration tools (Dagster or Airflow)
Live in New York (or willing to relocate)
