Coordenador de Ciência de Dados leading the data team in developing analytical solutions for Caixa Vida e Previdência. Focused on data science and project coordination in a collaborative environment.
About the role
- Data Scientist analyzing complex datasets to drive business decisions around credit risk and fraud at Clara. Join the fastest-growing fintech in LATAM and support financial clarity for businesses.
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
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