Senior Data Scientist

This is a fully remote position, open to applicants in Brazil.

📋 Description

• Create credit risk models that enhance analytical and lending capabilities within agribusiness.

• Establish technical methodologies, frameworks, and standards for model development and analytical workflows.

• Clearly document and convey results in an actionable manner to various audiences and stakeholders.

• Lead presentations and feedback sessions with both internal and external clients.

• Work alongside Engineering and Product teams to identify needs and uncover opportunities for model-driven enhancements.

• Investigate new variables and data sources to boost the predictive accuracy of models.

• Assess and integrate new techniques and technologies to enhance the efficiency and precision of risk solutions.

• Ensure alignment between data science technical choices and business goals.

• Act as a technical resource for data scientists and analysts, aiding in methodological decisions and conducting reviews of code and models.

• Guide the advancement of risk model architecture, focusing on features, validation, monitoring, and MLOps.

• Evaluate trade-offs between complexity, performance, interpretability, and model governance.

• Assist in the technical planning of medium- and long-term analytical projects.

⛳️ Requirements

• Strong expertise in Machine Learning as applied to real-world credit and risk challenges, including model validation, bias management, temporal stability, and explainability.

• Practical experience in feature engineering and assessing variable impact in live production settings.

• Capability to review, enhance, and elevate the quality of analytical code with an emphasis on efficiency and reproducibility.

• Background in credit risk modeling.

• Involvement in analytical architecture discussions concerning data, models, and workflows.

• Skillful in querying and manipulating databases for model development and validation.

• Familiarity with Git and Bitbucket.

• Strong and clear communication abilities to present technical findings to diverse audiences.

• Capacity to operate both independently and collaboratively within multidisciplinary teams.

• Preferred qualifications: experience in software engineering and ML engineering; a critical view on LLMs and AI agents; experience in agile environments; knowledge of Node or Java; Hadoop, Spark/PySpark, or Polars; familiarity with cloud platforms, preferably GCP.

• Bachelor’s degree.

🏝️ Benefits

• Meal/Food allowance.

• Wellhub (Gympass).

• Uniodonto (dental plan).

• Flexible benefits card.

• Childcare assistance.

• Life insurance.

• Language tuition assistance.

• Pet Life and Dog Life.

• English Pass.

• Unimed (health plan).