What you will be doing
Our Data Science team is high-impact. Our models directly impact budget planning, marketing spend allocation, and product prioritization. We're building an agentic AI ecosystem that shapes how we research, ship, and monitor across the company.
We're hiring a Senior Data Scientist with strong NLP and ML skills. You'll build classification, scoring, and prediction models across both B2B and B2C domains - lead prediction, account health monitoring, revenue and marketing forecasting, and extracting signals from unstructured user data. You'll also contribute to the team's AI ecosystem, including evaluating and calibrating AI agent outputs, and work on ML projects across our revenue and marketing portfolio.
Our stack: Python, BigQuery, GCP, our own production pipeline framework, Prefect, and Grafana.
We're looking for someone with strong modeling instincts who cares about business impact - not just technical depth, but making sure the work lands and changes how decisions are made.
- Build classification, scoring, and prediction models across B2B and B2C domains - lead scoring, account health monitoring, user segmentation, among owning ML projects across the team's portfolio
- Design text-based features from noisy, real-world user data - prompts, project metadata, usage patterns — where off-the-shelf embeddings aren't necessarily enough and domain-specific signal extraction matters
- Evaluate, calibrate, and improve AI agent outputs - measuring accuracy, and identifying failure modes in AI-generated results
- Lead projects end-to-end: from identifying a business problem with stakeholders, through DS project planning and research, to production deployment and integration
- Apply DS solutions to solve business problems across Finance, Marketing, Product, and other internal teams
Your skills and experience
- M.Sc. or Ph.D. in Statistics, Computer Science, Mathematics, or a related quantitative field
- 5+ years of hands-on data science experience
- Proven experience deploying NLP or text-based models into production environments
- Strong programming skills in Python and SQL (BigQuery or equivalent)
- Experience with ML frameworks; familiarity with time-series methods is a plus
- End-to-end project experience: from business problem definition through research, modeling, production, and stakeholder delivery
- Proven experience working with both unstructured and structured data
- Daily use of AI tools in your workflow - you already work with LLMs, coding assistants, or AI-powered tooling as a natural part of how you get things done
- Strong communication skills - ability to present complex technical findings clearly to non-technical audiences, and collaborate effectively across teams
Good to haves
- Experience with anomaly detection or unsupervised methods
- Experience evaluating, calibrating, or benchmarking LLM and AI agent outputs
- Fine-tuning or RAG production experience