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Konfio is Mexico's leading fintech company serving over 100,000 SME clients with financing, corporate credit cards, and payment solutions. You will design, implement, and operate machine learning and AI models—including LLMs and agentic systems—to optimize risk underwriting and customer management strategies.
Key Responsibilities:
• Model Development: Build predictive models and ML algorithms for customer origination and management, leveraging alternative data sources such as electronic invoicing.
• Experimentation: Run rigorous experiments including A/B testing, champion-challenger frameworks, and causal inference. Evaluate LLMs in the development lifecycle using quality evaluation frameworks.
• MLOps & Monitoring: Write scalable Python code to track model drift and trigger retraining. Partner with ML Engineers and technical teams 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). Mentor junior data scientists.
You will work in a high-performance, C-level-facing environment that values GRIT, critical thinking, strategic execution, and responsible AI use. You will have direct impact on credit risk assessment and core business value, and lead practical integration of generative AI and emerging technologies.
Requirements:
• Education & Experience: Bachelor's degree in a quantitative STEM field with 5+ years of analytics experience (or Master's degree 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), MLOps practices, and advanced English proficiency.
