Senior Data Scientist
Role details
Job location
Tech stack
Job description
Our data science team sits at the center of Rain's product. We're a small, senior team embedded in a fast-moving fintech, which means the models we build go directly into production decisions - credit risk scoring, balance forecasting, personalized financial insights - and the impact is immediate and measurable.
We work closely with product, engineering, and compliance, and we operate like owners: defining problems, building solutions, and monitoring them in production. If you're the kind of data scientist who gets energized by seeing your work move the needle on a real product - not just a dashboard - this team was built for you.
This role is based remotely in EMEA. You'll be a key early hire on our international data science presence, working across time zones with our U.S.-based team and contributing to how we scale our ML function globally.
What You'll Do
- Run end-to-end experiments: feature engineering, model selection, A/B testing, and production monitoring
- Build and maintain scalable, well-documented pipelines that keep models healthy in production
- Design, train, and deploy ML and Agentic models that drive core product decisions, including credit risk, forecasting, and personalized recommendations
- Collaborate with product and engineering to translate business problems into well-scoped modeling tasks
- Communicate model behavior and findings to both technical and non-technical stakeholders
Requirements
- You thrive in ambiguity - you can take a loosely defined business problem, ask the right questions, and turn it into a well-scoped modeling task without waiting for a perfect brief
- You are a strong cross-functional collaborator who builds trust with product, engineering, and compliance partners and can speak their language
- You have a bias toward shipping - you know when a model is good enough to get into production and how to iterate from there, rather than optimizing in isolation
- You take ownership end-to-end: from a messy raw dataset to a monitored production model, you don't hand things off and walk away
- You communicate with clarity - you can walk a skeptical stakeholder through a model's tradeoffs without leaning on jargon
- You care deeply about model behavior in the real world, not just on a held-out test set
- You mentor and elevate the people around you, and you're energized by working somewhere where the stakes are real
Required Technical Qualifications
- Python and core ML libraries, (pandas, scikit-learn, PyTorch, or TensorFlow )
- SQL and working with large, complex datasets
- Experience with LLMs and NLP techniques (fine-tuning, RAG, prompt engineering or similar)
- Communication skills to explain models trade offs
- Solid understanding of statistical modeling, experimentation, and model evaluation
- Experience taking models from prototype to production
- Familiarity with agentic frameworks (e.g. Langchain) and agent orchestration and evaluation
Diversity, Equity and Inclusion Commitments