Senior Data Scientist – Risk Modeling (Senior Data Scientist – Modelado de Riesgos) - Hybrid
About this role
Analytical professionals who thrive in fast-paced financial environments will find a strong fit within Clara's Risk Data Science team. The organization builds the core financial infrastructure and corporate payment solutions utilized by thousands of growing businesses across Latin America, operating across hybrid models in regional hubs.
In this capacity, the incoming specialist will own the entire modeling lifecycle for credit risk. Responsibilities include designing predictive models for underwriting and portfolio management, leveraging Python and SQL to analyze large datasets, and partnering closely with Engineering and Finance to deploy robust scoring solutions throughout Mexico, Brazil, and Colombia.
What you will do
- Design, build, validate, and maintain predictive models for credit origination, behavioral risk, and portfolio management.
- Manage the complete model lifecycle from problem definition and feature engineering to backtesting and ongoing calibration.
- Utilize Python and SQL to query large datasets, investigate delinquency trends, and shape actionable credit strategies.
- Construct comprehensive monitoring frameworks to track model stability, data drift, and key performance indicators.
- Collaborate with Engineering and Data teams to ensure seamless deployment and integration of models into business systems.
- Communicate intricate analytical insights clearly to Risk leadership and other non-technical stakeholders.
What you need
- Possess four to six or more years of professional experience in Data Science, Risk Analytics, or Credit Risk roles.
- Demonstrate at least two years of hands-on involvement in developing or validating credit risk and predictive models.
- Bring strong technical proficiency in Python and SQL for statistical analysis and data manipulation.
- Have prior experience utilizing Databricks or comparable cloud-based analytics platforms.
- Apply familiarity with machine learning libraries such as scikit-learn, LightGBM, XGBoost, or PyTorch.
- Maintain working proficiency in both English and Spanish.
- Hold an academic background in Statistics, Mathematics, Economics, Engineering, Computer Science, or a related quantitative discipline.
Nice to have
- Experience in fintech, lending, credit cards, payments, or B2B financial products
- Experience with Latin American credit markets, particularly Mexico, Brazil, or Colombia
- Experience with PD modeling, expected loss, ECL, LGD, or EAD methodologies
- Experience with MLflow, model registries, version control, and reproducible ML workflows
- Master’s degree in Statistics, Data Science, Machine Learning, Economics, Finance, or a related quantitative field
Benefits
- Competitive salary and stock options from day one
- Multicultural team with daily exposure to Portuguese, Spanish, and English
- Annual learning budget and internal accelerated development paths
- Flexible vacation and hybrid work model focused on results
Skills and tech stack
Questions candidates ask
What is the work model for this position?
The role operates under a hybrid work model focused on results. Offices are located in Bogota D.C., Mexico City, and Sao Paulo.
What tools and technologies will I be using?
You will develop in a modern machine learning environment utilizing Databricks, MLflow, GitHub, Python, SQL, scikit-learn, and other appropriate modeling tools.
What kind of experience is required for this role?
Candidates need 4 to 6+ years of experience in Data Science, Risk Analytics, or Credit Risk, including at least 2 years of hands-on experience developing or validating credit risk models.
What benefits are provided upon joining?
Clara offers a competitive salary and stock options from day one, an annual learning budget, internal accelerated development paths, and flexible vacation.