Empresa: Stefanini
At Stefanini Group, we believe in the power of collaboration. We co-create innovative solutions in partnership with our clients, combining cutting-edge technology, artificial intelligence, and human creativity. We are at the forefront of solving business challenges, delivering real impact on a global scale. By joining Stefanini, you become part of a global journey of transformation. We are committed to creating a positive impact not only on businesses, but also in the lives of our employees. If you are looking for an opportunity for professional growth in a company that values innovation, respect, autonomy, and partnership, you will find it here! Join us and be part of the change! Work Model: Hybrid (twice a week at Eusébio Matosso, São Paulo/SP). #LI-JS2 • Advanced Statistical & Predictive Modeling: Develop predictive models for churn, detraction propensity, and customer behavior using logistic regression, gradient boosting, survival analysis, and multivariate modeling. • Next Best Offer (NBO) / Recommendation Systems: Build cross-sell, up-sell, and next-best-action models, measuring incremental business impact through A/B testing, control groups, and uplift modeling. • Data Architecture & Analytics Governance: Design data models, define data dictionaries, quality rules, and ensure data integrity across complex enterprise pipelines (CRM, ERP, ITSM) while ensuring LGPD/GDPR compliance. • Insights & Executive Storytelling: Translate complex statistical outputs and machine learning models into clear executive dashboards, actionable operational triggers, and business recommendations for leadership. Requisitos: • Bachelor's degree in Statistics, Mathematics, Data Science, Economics, or Engineering . • Solid experience (5+ years) in statistical modeling, data science, and advanced data analytics . • Strong technical stack: Python (pandas, scikit-learn, statsmodels) or R; Advanced SQL ; Dimensional modeling, ETL, and data governance ; Experience with Power BI or Tableau . • Strong command of machine learning validation metrics (AUC, precision, recall, lift) , hypothesis testing, and sample design . • Languages: Advanced English (mandatory) and Intermediate Spanish (desirable) . Nice to Have (Differentials): • Post-graduate degree or Master's in Statistics, Data Science, or quantitative fields . • Prior domain knowledge or experience in Customer Experience (NPS, CSAT, CES), Customer Success, CRM analytics, or customer retention . • Experience with PySpark, Databricks, Snowflake, Azure Data Factory, BigQuery, MLOps, or NLP/LLMs applied to customer feedback .