Senior Data Scientist – Credit Risk Modeler, Databricks

Job not on LinkedIn

🔥 18 hours ago

🇲🇽 Mexico – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 17%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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MUTT DATA

WebsiteLinkedInAll Job Openings

51 - 200 employees

📣 Marketing

🛡️ Insurance

📦 Logistics

Marketing • Insurance • Logistics

MUTT DATA is a consulting firm that specializes in leveraging AI and machine learning to create automated systems that drive revenue for their clients. They offer solutions in sectors such as Adtech, Martech, Fintech, and Telecommunication, focusing on optimizing advertising platforms, enhancing data-driven marketing strategies, and providing real-time insights in financial and telecommunications networks. MUTT DATA provides expert team augmentation, seamless integration of data architectures in the cloud, and tailor-made solutions to refine product strategies. Their services include implementing modern data stacks, marketing mix modeling, and generative AI. MUTT DATA partners with leading companies like Amazon Web Services, Google Cloud, and others to deliver advanced data and AI solutions. They are recognized in LATAM for their AWS competencies and expertise in data science and MLOps, ensuring robust, scalable, and cost-effective data systems for their clients.

📋 Description

• Take ownership of the existing tree ensemble / gradient boosting model • Retrain the model and incorporate new features, such as digital payments and CISP • Evaluate performance using AUC-ROC, F1, and probability calibration • Segment risk levels A–F aligned with credit standards • Calculate dynamic credit lines and expected loss / risk exposure • Integrate score, potential, and sales history • Package the model under the MFL framework using PyFunc, model cards, and tests for productionization • Work closely with data and platform teams • Maintain and responsibly evolve a live financial model

🎯 Requirements

• Proven experience in credit risk / scoring models and supervised machine learning • Python proficiency, including scikit-learn and XGBoost • Knowledge of statistics and model validation • Experience with MLflow • Understanding of risk metrics, including probability of default (PD), expected loss, and exposure • Experience in financial services, credit bureaus, or commercial credit portfolios (nice to have) • Experience developing AI agents / agentic infrastructure, such as Mosaic AI Agent Framework, agent orchestration, or MCP (nice to have)

🏖️ Benefits

• Remote-first work environment • Continuous learning • Collaboration-focused culture • Positive mindset and open team-player culture