Mid-level Data Scientist

📋 Description

• Design, evaluate, and enhance machine learning models related to credit, fraud, risk, and user behavior.

• Investigate innovative techniques, features, and analytical methods with an emphasis on tangible business outcomes.

• Engage in the entire model lifecycle from conception to execution, including the design, implementation, and upkeep of data and ML pipelines in a production setting, ensuring reliability and efficiency.

• Collaborate closely with Engineering, Product, and Risk teams to convert business challenges into analytical solutions and scalable models.

• Conduct exploratory analyses, tests, experiments, and assessments of model performance.

• Track business metrics and model efficacy, assisting in the identification of enhancement opportunities.

• Aid in establishing development best practices, version control, and maintaining the team's technical excellence.

⛳️ Requirements

• Previous experience in Data Science, Machine Learning, or Analytics.

• Strong understanding of statistics, predictive modeling, and data analysis.

• Proficiency in Python and machine learning libraries.

• Knowledge of supervised models, feature engineering, and model evaluation techniques.

• A passion for exploring new methodologies and a commitment to continuous learning.

• An analytical and pragmatic mindset, with comfort in fast-paced environments that undergo rapid changes.

• Effective communication skills and a collaborative spirit across various teams.

• Preferred: Background in fintech, credit, fraud, risk, or payments.

• Experience in deploying models to production or familiarity with MLOps practices.

• Understanding of gradient boosting, neural networks, Graph Neural Networks, or LLMs.

• Proficient in SQL and managing large datasets.

• Experience with cloud computing environments.

• Familiarity with tools such as Airflow, MLflow, Feast, or similar.

• Advanced proficiency in English.

🏝️ Benefits

• Health plan covering 100% of the employee and 75% for the first dependent.

• iFood Benefits.

• Day off during your birthday month.

• Group life insurance.

• Discount coupons at our partner stores.

• Remote work model.