Senior Data Scientist

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

📋 Description

• Create predictive churn models to pinpoint customers likely to withdraw investments and transfer their funds to other financial institutions.

• Conduct exploratory data analysis, engage in feature engineering, and carry out model training, validation, and optimization of Machine Learning models.

• Construct customer segmentation models to uncover behavioral patterns and possible reasons for attrition.

• Develop recommendation engines that aid in customer win-back and retention strategies.

• Create investment portfolio optimization solutions while considering risk profiles, liquidity, concentration, investment horizons, and suitability rules.

• Utilize model explainability techniques, such as SHAP, to ensure transparency and traceability of predictions.

• Execute temporal validation, backtesting, and model performance evaluation processes.

• Work with financial data sourced from internal systems, Open Finance, and investment information.

• Develop and operationalize models within Azure Databricks, utilizing MLflow, Unity Catalog, and Feature Engineering capabilities.

• Collaborate on establishing batch inference pipelines, model monitoring, and MLOps processes.

• Assist in integrating analytical models with generative AI solutions to generate business insights.

• Prepare technical documentation and facilitate model validation and governance processes with clients.

⛳️ Requirements

• Extensive experience as a Data Scientist, with practical knowledge in developing and deploying Machine Learning models.

• Proficient in Python and SQL for effective data manipulation, analysis, and modeling.

• Familiarity with Data Science libraries such as Pandas, NumPy, Scikit-learn, and XGBoost or comparable tools.

• Experience with supervised classification models, churn prediction, and customer segmentation methodologies.

• Understanding of feature engineering, feature selection, temporal validation, and hyperparameter optimization techniques.

• Knowledge of predictive model evaluation metrics, probability calibration, and explainability techniques.

• Practical experience with Databricks for the development and execution of analytical models.

• Familiarity with MLflow for experiment tracking, version control, and managing the model lifecycle.

• Knowledge of mathematical optimization techniques relevant to problems with multiple constraints.

• Experience in developing reproducible models, drafting technical documentation, and adhering to robust governance practices.

• Ability to collaborate with business teams to understand issues, define analytical strategies, and translate findings into actionable recommendations.

• Possess an analytical, investigative, and problem-solving approach, capable of tackling complex challenges.

🏝️ Benefits

• Remote work options available.

• Mental Health Program offering online and in-person psychotherapy.

• Support for professional certifications and courses.

• Partnerships for postgraduate and MBA programs (Esalq/USP).

• Collaborations with language schools.

• Partnerships with gyms and wellness applications (Wellhub).

• Internal talks and discussion groups for continuous learning.

• Employee referral bonus incentives.

• Social events like happy hours.

• Gifts and treats provided during special occasions.