Cientista de Dados SR in Brazil at Jobgether

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Cientista de Dados SR based in Brazil.

This is an opportunity for a senior Data Scientist to build and evolve data-driven solutions for complex business challenges in supply chain, inventory, and product distribution.
You will design allocation and optimization algorithms that directly influence service levels, inventory availability, and operational efficiency.
The role combines advanced data science, statistical modeling, large-scale data processing, and cloud engineering.
You will transform analytical prototypes into reliable, scalable production solutions and work closely with data engineering and business teams.
Your work will involve high-volume datasets, simulation, forecasting, optimization, and what-if analysis to support strategic decisions.
The environment values technical excellence, continuous improvement, knowledge sharing, and strong collaboration with diverse stakeholders.
This is a strong fit for someone who enjoys connecting sophisticated analytical models with measurable business impact.

• Develop, implement, and continuously improve allocation and optimization algorithms for distributing products across distribution centers and stores.
• Maintain and enhance inventory simulators used for scenario analysis, replenishment policy testing, backtesting, and what-if simulations.
• Transform data science prototypes and notebook-based models into scalable, maintainable, and production-ready solutions.
• Build, maintain, and optimize large-scale data pipelines that support analytical and operational models.
• Analyze business indicators such as service level, stockouts, inventory turnover, and fill rate, translating findings into actionable strategic recommendations.
• Communicate analytical results, recommendations, and improvement opportunities clearly to business stakeholders and technical teams.
• Partner with Data Engineering teams to build, operate, and evolve cloud-based pipelines, particularly within AWS environments.
• Ensure the quality, reliability, scalability, and performance of analytical solutions running in production.
• Contribute to the continuous evolution of replenishment, supply planning, and inventory management models and practices.
• Help define and implement best practices across Data Science, analytical engineering, and scalable solution development.
• Where applicable, provide technical leadership and mentorship to other Data Scientists and contribute to the development of the broader data community.

• Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, Economics, or a related field.
• Solid professional experience in Data Science, including the development and implementation of solutions addressing real-world business challenges.
• Advanced Python skills, including strong experience with libraries such as NumPy and Pandas.
• Strong SQL skills for querying, manipulating, and analyzing data.
• Solid knowledge of statistics and probability applied to forecasting, inventory management, and service-level metrics.
• Hands-on experience with PySpark for processing and transforming large volumes of data.
• Proven experience building, maintaining, and optimizing large-scale data pipelines.
• Experience with AWS services, particularly AWS Glue and Amazon S3.
• Strong analytical and problem-solving capabilities, with the ability to turn complex data into actionable insights and strategic recommendations.
• Excellent communication skills and the ability to collaborate effectively with both technical teams and business stakeholders.
• Knowledge of Polars, Numba/JIT optimization, allocation algorithms, optimization, or operations research is a strong plus.
• Experience with multi-echelon inventory simulation, replenishment strategies, Streamlit, Plotly, Terraform, Infrastructure as Code, CI/CD, or AWS Step Functions is desirable.
• Experience providing technical leadership or mentoring Data Scientists is an additional advantage.

• Opportunity to work on complex, high-impact data science challenges with direct business impact.
• Exposure to large-scale data, cloud technologies, optimization, simulation, and advanced analytical solutions.
• Collaborative environment focused on innovation, continuous learning, and technical excellence.
• Opportunities for technical leadership, mentoring, and professional development.
• Interaction with multidisciplinary teams and stakeholders across different business areas.
• Opportunity to contribute to scalable production solutions rather than working exclusively with experimental models.
• A diverse and collaborative culture that encourages knowledge sharing and continuous growth.