Job Description

Who are we?

We are Mexico's leading financial technology company, empowering over 100,000 clients to achieve their business goals. Our mission is to fuel the growth of small and medium-sized enterprises (SMEs) through innovative solutions—including financing, corporate credit cards, and payment systems. We partner with entrepreneurs to help them overcome challenges, transforming their businesses into true engines of economic growth while contributing to the development of our community, our country, and the planet.

About the Role

You will design, implement, and operate Machine Learning and AI models—including LLMs and agentic systems—to optimize our risk underwriting and customer management strategies. You will drive continuous experimentation, monitor model performance, ensure strict governance compliance, and translate data into strategic business decisions while mentoring junior data scientists.

Key Responsibilities

• Model Development: Build predictive models and ML algorithms for customer origination and management, leveraging alternative data sources like electronic invoicing..
• Experimentation: Run rigorous experiments (A/B testing, champion-challenger, causal inference) and evaluate LLMs in the development lifecycle using quality evals..
• MLOps & Monitoring: Write scalable Python code to track model drift and trigger retraining. Partner with ML Engineers and Tech to automate CI/CD pipelines, versioning, and production deployments..
• Governance: Enforce model governance standards, ensuring comprehensive documentation, validation, explainability, bias analysis, and regulatory compliance..
• Communication & Mentoring: Translate complex technical findings for executive leadership and cross-functional teams (Credit, Product, Business), and mentor junior data scientists.

Required Profile

• Education & Experience: BS in a quantitative STEM field with 5+ years of analytics experience (or Master's with 2+ years). Minimum 3 years of proven experience as a Data Scientist..
• Technical Stack: Advanced object-oriented Python (Pandas, scikit-learn), complex SQL, and Git. Experience extracting and analyzing large datasets (Big Data)..
• ML & Statistics: Deep expertise in supervised/unsupervised models, deep learning, causal inference, and statistical fundamentals. Hands-on experience with LLMs, foundational models, and agentic systems via APIs or open-source tools.
• Desirable: Financial sector experience operating Risk and Collections models, cloud platforms (AWS), and MLOps practices. Advanced English proficiency.

Value Proposition

• Impact at Scale: Build analytical solutions that directly shape credit risk assessment and drive core business value..
• Cutting-Edge Innovation: Lead the practical integration of Generative AI and emerging technologies to elevate our data science capabilities..
• Strategic Collaboration: Work closely with Credit, Product, and Tech teams to ensure technical viability aligns with real market needs..
• Culture of Excellence: Join a high-performance, C-Level-facing environment that values GRIT, critical thinking, strategic execution, and the responsible use of AI..