Lead Data Scientist | Forecasting & Decision Intelligence
BrazilFull-TimeLead
Salary not disclosed
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Job Details
- Languages
- Advanced English skills
- Required Skills
- PythonMachine LearningData scienceSparkDatabricks
Requirements
- Solid experience in Data Science applied to complex business challenges.
- Proven experience developing, improving, and deploying demand forecasting models using time series analysis in production environments.
- Strong knowledge of statistics, probability, quantitative modeling, and linear algebra applied to real-world problems.
- Advanced proficiency in Python for model development, feature engineering, validation, deployment, and production monitoring.
- Experience with Databricks and its ecosystem, including Spark, Delta Lake, Unity Catalog, and machine learning pipelines.
- Advanced English skills for frequent collaboration with international teams.
- Strong analytical mindset with the ability to connect technical solutions with business outcomes.
- Ability to work autonomously in a fast-paced technology environment.
Responsibilities
- Develop, improve, and scale advanced demand forecasting models to support better planning and management of perishable products.
- Own the full lifecycle of data science projects, including data exploration, feature engineering, model development, validation, deployment, monitoring, and continuous improvement.
- Build intelligent recommendation systems that transform demand predictions into actionable purchasing and operational decisions.
- Translate complex business challenges into robust quantitative models by applying statistical methods, machine learning techniques, and mathematical modeling.
- Ensure model quality, scalability, governance, and performance in production environments using modern data platforms and machine learning ecosystems.
- Collaborate closely with technology and product teams to define priorities and evolve data-driven solutions.
- Contribute to the development of innovative capabilities in analytics, forecasting, and decision intelligence.
- Apply best practices in data science engineering, experimentation, and model lifecycle management.
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