🚀 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.
- 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.
- Amazon Web Services
- Astronomer
- Databricks
- 📊 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 our blog 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.
- 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).
- Mandatory: Hands-on experience with Databricks applied to credit models, credit risk, or credit scoring.
- 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).