Hybrid Data Scientist – Riesgo

at Clara

• Job title: Data Scientist – Riesgo
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Cloud, Python, PyTorch, Scikit-Learn, SQL
• Location requirements: Hybrid, Bogota, Colombia

About the role

• Data Scientist at Clara analyzing datasets for credit risk and fraud prevention. Collaborating cross-functionally to develop data-driven strategies for business growth.

Responsibilities

• Define and solve complex problems: Collaborate with cross-functional teams to identify business challenges, propose end-to-end solutions, and execute strategies that align with company objectives.
• Drive data understanding and insights: Explore and interpret large datasets using SQL and Python to identify patterns, anomalies, and trends. You will translate these findings into actionable insights that support informed decision-making.
• Build and deploy predictive models: Design, develop, and monitor machine learning models using Databricks, MLflow, scikit-learn, and PyTorch. You will follow the CRISP-DM methodology to ensure rigorous modeling standards from conception to production.
• Ensure data quality and integrity: specific responsibilities include cleaning and transforming raw data to ensure it is suitable for analysis, applying data quality checks, and maintaining validation rules.
• Innovate and automate: Continuously monitor model performance and data drift while staying updated on advancements in AWS cloud infrastructure and statistical methods to refine our analytical approaches.

Requirements

• 5+ years of experience in data science or analytics, with a minimum of 2 years of hands-on experience developing risk models (e.g., credit, fraud, or churn).
• Strong technical proficiency in Python and SQL for data manipulation, querying, and statistical analysis.
• Proven experience working with cloud-based platforms, specifically AWS and Databricks.
• Hands-on experience with ML platforms and libraries such as MLflow, scikit-learn, and PyTorch.
• Working proficiency in English and Spanish.
• Strong problem-solving abilities with the capacity to communicate complex modeling processes to non-technical stakeholders.
• A degree in Data Science, Computer Science, Mathematics, Statistics, or equivalent practical experience.
• Adaptability to fast-changing, high-growth environments.

Benefits

• Competitive salary and stock options (ESOP) from day one
• Multicultural team with daily exposure to Portuguese, Spanish, and English (our corporate language)
• Annual learning budget and internal accelerated development paths
• High-ownership environment: we move fast, learn fast, and raise the bar — together
• Smart, ambitious teammates — low ego, high impact
• Flexible vacation and hybrid work model focused on results