• Use SQL, Python, or other analytical tools to query, clean, and analyze large datasets. • Analyze labor market trends across dimensions such as workforce composition, job demand, employment patterns, and wage dynamics. • Apply advanced techniques including time series forecasting, clustering, regression analysis, and machine learning algorithms (e.g., decision trees, random forests, gradient boosting, support vector machines, k-means clustering) to identify patterns and forecast labor trends. • Build and maintain scalable data and model pipelines using orchestration tools like Apache Airflow, Luigi, or Sagemaker Pipelines, and model tracking tools such as MLflow. • Collaborate cross-functionally to define problem statements, gather and analyze data, integrate models into products, and translate insights into actionable recommendations for technical and non-technical audiences. • Stay informed on advancements in labor market analytics, statistical modeling, and machine learning technologies.

• Support the Diagnostics Platform by contributing to the strategy, development, and operationalization of LLMs, agentic AI, and image AI solutions • Lead assay development optimization and R&D process acceleration using advanced statistical and ML methods • Conduct RWE analytics of EHR/claims/registries/device telemetry to drive biomarker discovery and development • Implement reliable and reproducible AI frameworks that improve diagnostic performance analytics, workflow efficiency, labeling/claims support, HEOR/RWE insights, image processing, and customer experience • Translate analyses into clear, concise narratives, dashboards, and cross‑functional updates

• Work on new directions and solutions for the market • Look for ways to improve existing algorithms • Introduce and experiment with new data sources • Collaborate with data engineers and product teams

• Provide support to the demand planning team by producing forecasts and conducting statistical analyses. • Build models that will guide the sales plan, based on a clear, data-driven rationale. • Develop demand forecasts and statistical/econometric studies using statistical modeling tools in R and Python. • Identify and ensure optimization of existing processes. • Manage the quality of solutions proposed by the team. • Identify and analyze events (marketing campaigns, dates, special events, etc.) and market, competitor, and customer information that may impact demand for Nestlé products. • Monitor the accuracy and performance of the models developed. • Support demand planners in the use and application of predictive models.