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Data Scientist (Statistical Modeling & Analytics)

πŸ•’ yesterday
Statistical ModelingPredictive ModelingPythonPandas
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πŸ“œ Description

  • Develop predictive models for churn, detraction propensity, and customer behavior using statistical and machine learning methods.
  • Build cross-sell, up-sell, and next-best-action models; measure impact through A/B testing, control groups, and uplift modeling.
  • Design data models, data dictionaries, and quality rules for enterprise pipelines, ensuring data integrity and LGPD/GDPR compliance.
  • Translate statistical and machine learning results into executive dashboards, operational triggers, and business recommendations.

πŸ› οΈ Requirements

  • 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).
  • 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.
Full job description

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 EusΓ©bio Matosso, SΓ£o Paulo/SP).

#LI-JS2

Responsibilities

  • 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.

Requirements

  • 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.


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