Develop data science and machine learning solutions to solve business problems, working from problem understanding through delivery of models/insights, using Python, BigQuery and Vertex AI (when applicable);
Translate business problems into hypotheses, metrics and analytical experiments;
Perform advanced EDA, feature engineering and preparation of training datasets;
Train and evaluate models (classification, regression, time series, clustering, recommendation as required);
Implement training/inference pipelines (e.g., notebooks + Vertex AI pipelines, when applicable);
Support initial deployment and handoff to production with engineering/MLOps (endpoints, batch scoring, scheduled jobs);
Document experiments (metrics, data/model versions, decisions) and support monitoring (drift/performance, when applicable);
Contribute to components of AI agents (e.g., features, scoring, intelligent rules, agent performance evaluation).

Bachelor's degree completed;
Intermediate/advanced Python (pandas, numpy, scikit-learn; notebooks);
Applied statistics and ML fundamentals (validation, overfitting, metrics);
Advanced SQL and experience with BigQuery;
Familiarity with GCP and ML (desired: Vertex AI, pipelines, endpoints);
Version control with Git and good reproducibility practices;
Differentials: MLflow/experiment tracking, model registry, LLM/Generative AI (when applicable), MLOps fundamentals;
Statistical and ML modeling; validation and metrics;
Feature engineering and robust data preparation;
Critical interpretation of results and translation to business insights;
Good reproducibility practices (versioning, documentation).
Critical thinking and analytical rigor;
Proactivity and scientific curiosity;
Clear communication with technical and non-technical audiences;
Collaboration with engineering/product/business teams.

Health and Dental Plan – Bradesco – coverage extendable to dependents
PAE – Financial assistance available for dependent children and/or stepchildren with intellectual disabilities
Pharmacy partnership – discounts up to 85%
Complementary Pension – FlexPrev plan – contributions ranging from 1% to 11%, depending on salary
Life Insurance – coverage for all employees from the hire date, no employee contribution
Extended Leaves – Maternity leave (total 180 days) and Paternity leave (total 20 days)
Meal and/or Food Allowance – Caju Benefits
Educational Assistance – for dependents up to high school
TotalPass
Solar Subscription – possibility of a special discount on the electricity bill through participation in a distributed generation plan
Corporate Smiles Club – discounts up to 50% on plans to help you plan your trips. Also available for spouse and children 18+.
Length-of-service bonus – an additional salary payment (based on tenure) paid at the time of vacation.

Data Scientist, Mid-level

Key skills