Senior Data Scientist - Credit Risk Modeler - #4 at Muttdata (Remote)Senior Data Scientist - Credit Risk Modeler - #4

🚀 Join Our Remote Data Products & Machine Learning Startup! 🚀 At Muttdata, we build innovative Data Products and Machine Learning solutions that help companies solve complex business challenges. As a fast-growing, remote-first startup, we're passionate about technology, collaboration, and continuous learning. This opportunity is with a leading multinational beverage company based in Mexico City. We are looking for a Senior Data Scientist  - Credit Risk Modeler to join our team 🐶🚀. You'll inherit, maintain, and evolve our Credit Score model (Hit / No Hit), applying credit-risk modeling expertise to segment the portfolio by probability of default and enable dynamic credit lines. This role works closely with data and platform teams, taking ownership of a live financial model and evolving it responsibly. Strong statistical rigor, business understanding of credit risk, and ownership are essential to succeed in this fast-paced, collaborative environment.

🚀 What We Do

• Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
• Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
• Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
• Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
• Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
• Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.

🌟 Our Partnerships

• Amazon Web Services
• Astronomer
• Databricks

🌟 Our Values

• 📊 We are Data Nerds
• 🤗 We are Open Team Players
• 🚀 We Take Ownership
• 🌟 We Have a Positive Mindset

🔍 Curious about what we’re up to? Check out our case studies and dive into ourblog post to learn more about our culture and the exciting projects we’re working on! 🚀

• Take ownership of the existing model (tree ensembles / gradient boosting), retrain it, and incorporate new features (e.g., digital payments, CISP).
• Evaluate performance (AUC-ROC, F1, probability calibration) and segment risk levels A–F aligned with credit standards.
• Calculate dynamic credit lines and expected loss (risk exposure), integrating score, potential, and sales history.
• Package the model under the MFL framework (PyFunc, model_card, tests) for productionization.

Required Skills 🚀

• Proven experience in credit risk / scoring models and supervised machine learning.
• Python (scikit-learn, XGBoost), statistics, model validation, and MLflow.
• Understanding of risk metrics (PD, expected loss, exposure).

• Experience in financial services, credit bureaus, or commercial credit portfolios.
• Experience developing AI agents / agentic infrastructure (e.g. Mosaic AI Agent Framework, agent orchestration, MCP).