Senior Data Scientist – Risk Modeling (Fintech)

Location: Hybrid roles based in Bogota D.C., Colombia; Mexico City, Mexico; or Sao Paulo, Brazil. Hybrid work includes time at the office, customer visits, and working from home.

Company

hirify.global builds B2B financial infrastructure for payments, corporate cards, bill pay, financing, and spend management across Latin America.

What you will do

• Design, build, validate, maintain, and implement predictive credit risk models for origination, behavioral risk, portfolio management, and related use cases.
• Own the model lifecycle, including problem definition, target construction, feature engineering, development, validation, backtesting, calibration, monitoring, recalibration, and documentation.
• Use Python and SQL to analyze large financial and transactional datasets, portfolio trends, delinquency, losses, and risk indicators.
• Develop underwriting strategies, score cutoffs, credit limits, segmentation, and portfolio management policies.
• Build monitoring and data quality frameworks covering model discrimination, calibration, stability, drift, vintages, roll rates, delinquency, and portfolio performance.
• Partner with Risk, Data, Engineering, Finance, Operations, and business stakeholders to deploy models and translate analytics into actionable decisions.

Requirements

• 4–6+ years of experience in Data Science, Risk Analytics, Credit Risk, or related analytical roles, including at least 2 years developing or validating credit risk or predictive risk models.
• Strong Python and SQL skills and experience with Databricks or a similar cloud analytics platform.
• Experience with predictive modeling libraries such as scikit-learn, LightGBM, XGBoost, PyTorch, or equivalent tools.
• Understanding of credit risk analytics, including delinquency, default, vintage analysis, roll rates, bad rates, discrimination, calibration, and population or model stability.
• Experience with large financial or transactional datasets, data quality, model lifecycle practices, and translating quantitative analysis into business recommendations.
• Working proficiency in English and Spanish. Academic background in a quantitative field such as Statistics, Mathematics, Economics, Engineering, Computer Science, Actuarial Science, or Data Science.

Nice to have

• Experience in fintech, lending, credit cards, payments, or B2B financial products.
• Knowledge of Latin American credit markets, especially Mexico, Brazil, or Colombia.
• Experience with credit bureau data, alternative data, PD, ECL, LGD, EAD, reject inference, or selection bias.
• Experience defining credit line strategies, cutoffs, risk segmentation, underwriting policies, or implementing models with Engineering.
• Experience with MLflow, GitHub, data pipelines, Metabase, or a relevant master’s degree.

Culture & Benefits

• Product-led, inclusive, values-driven environment focused on ownership, clarity, simplicity, and continuous improvement.
• Multicultural team with daily exposure to Portuguese, Spanish, and English.
• Competitive salary and stock options through ESOP from day one.
• Annual learning budget and accelerated internal development paths.
• Flexible vacation and a hybrid work model focused on results.