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
Diversity, Equity and Inclusion Commitments
As part of our dedication to the diversity of our workforce, Rain is committed to Equal Employment Opportunity and does not discriminate based on race, religion, color, national origin, ethnicity, gender, sex (including pregnancy), protected veteran status, age, disability, sexual orientation, gender identity, gender expression, or any unlawful criterion existing under applicable federal, state, or local laws. If you need assistance or accommodation due to a disability, you may contact us at [email protected].
What’s Next
Ensuring a smooth and enjoyable candidate experience is critical for us. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don’t be afraid to let us know if you need more flexibility.
Diversity, Equity and Inclusion Commitments
As part of our dedication to the diversity of our workforce, Rain is committed to Equal Employment Opportunity and does not discriminate based on race, religion, color, national origin, ethnicity, gender, sex (including pregnancy), protected veteran status, age, disability, sexual orientation, gender identity, gender expression, or any unlawful criterion existing under applicable federal, state, or local laws. If you need assistance or accommodation due to a disability, you may contact us at [email protected].
What’s Next
Ensuring a smooth and enjoyable candidate experience is critical for us. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don’t be afraid to let us know if you need more flexibility.
Skills Required
- 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)
- 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
- Communication skills to explain model trade-offs to technical and non-technical stakeholders
What We Do
Rain Technologies Inc. provides an AI-driven financial health platform for employers and employees, offering earned-wage access, budgeting tools, financial coaching, and balance-protection features. The platform integrates with payroll systems, emphasizes enterprise security and minimal data collection, and aims to reduce employee financial stress, improve retention, and increase productivity across industries such as retail, hospitality, and healthcare.
