Senior Data Scientist

About Us

Rain is the world's first AI Financial Health Platform, serving 3.5 million employees at leading organizations like McDonald's, Marriott, and T-Mobile. Rain works in the background to optimize every employee's financial life to prevent shortfalls and build long-term stability. Backed by top investors including QED and Prosus, Rain has raised $150M in venture funding to fuel our next stage of hyper growth.

About The Team

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

Who You Are

• 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