A growth-stage company syncing warehouse data to the tools business teams rely on every day.
Forward Deployed Marketing Data Scientist
We’re building a bridge between the modern data warehouse and the sprawling set of marketing tools—email platforms, ad networks, CDPs, analytics suites—that go-to-market teams actually use. Marketing data projects that once took weeks of pipeline wrangling and brittle scripts should take hours, and our customers expect us to prove it inside their own stacks. This role sits at the intersection of forward deployment and deep analytical modeling, turning raw customer data into attribution models, audience predictions, and campaign measurement frameworks that run directly against Snowflake or PostgreSQL backends. You’ll embed with customers to design experiments, ship Python or R code that lives in production, and shape the product roadmap from the patterns you uncover in the field.
What they're looking for
- 5+ years of hands-on experience using Python (Pandas, PyTorch) or R to build models for marketing use cases—attribution, lift measurement, customer lifetime value, churn forecasting, or audience segmentation.
- Deep fluency with SQL on cloud data warehouses such as Snowflake or PostgreSQL, including query optimization on large event-level datasets.
- Proven ability to work directly with external marketing and data teams—scoping ambiguous problems, presenting technical results to non-technical stakeholders, and driving adoption of your work.
- Comfortable operating in a customer-facing, travel-light role that blends consulting, data science, and engineering; prior forward-deployed or solutions engineering experience is a strong plus.
- A bias for shipping end-to-end: you can stand up a proof-of-concept model, harden it for production schedules, and document what you built so others can extend it.