Senior Data Scientist (Forecasting)

• Senior Experience: 5 or more years of experience in Machine Learning, forecasting, or advanced analytics projects.
• Technical Proficiency: Advanced theoretical and practical knowledge of forecasting techniques, time series, and Machine Learning.
• Business Experience: Proven track record in real-world cases of demand forecasting, sales, commercial planning, or operations, preferably in B2B businesses.
• Ecosystem and Cloud: Advanced proficiency in Python and its standard Data Science ecosystem, along with experience in cloud platforms (preferably AWS).
• Good Practices: Regular use of methodologies and tools such as Git, testing, documentation, code structuring, and CI/CD.
• Communication and Language Skills: Ability to convey complex concepts to business stakeholders and a minimum B2 level of English.

• Experience with the MLOps ecosystem and tools such as MLflow, Kubeflow, SageMaker, or equivalent.
• Knowledge of advanced forecasting models: multivariate, probabilistic, hierarchical, or using deep learning for time series.
• Previous experience in industrial, commercial, logistics, supply chain sectors, or demand planning.

• Flexible compensation (Cobee) for restaurant, transportation, training, and childcare.
• Health insurance with Cigna, Adeslas, or Sanitas.
• Wellness program for emotional and psychological well-being.

We are looking for a Senior Data Scientist specialized in forecasting to join key projects involving demand and sales prediction in B2B environments. You will be part of our Data&AI team, with the challenge of designing, developing, and deploying Machine Learning models applied to real business problems, leading technical initiatives from start to finish.

Your daily tasks will include:

• Gather business requirements and define the analytical approach to address complex planning needs.
• Design, develop, and validate forecasting and Machine Learning models applied to real-world cases of demand, sales, commercial planning, or operations forecasting.
• Oversee the deployment of models into production, ensuring their robustness and proper performance in real-world environments.
• Communicate fluently with technical and business stakeholders, clearly explaining the results, limitations, and real impact of the models.
• Apply best practices in code development and analytical architecture to ensure scalable and maintainable solutions.

• 23 vacation days + December 24th and 31st off.
• 1 day for professional events and 3 days for personal errands (free conciliation days).
• Reduced hours in August and intensive workday every Friday of the year.
• 100% remote work: You will work remotely, with some flexibility to adjust your schedule, although it will depend on the project you are on.