Cientista de Dados Senior in Brazil, Indiana at Jobgether

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Cientista de Dados Senior in Brazil.

This role is focused on designing and delivering robust data science solutions that ensure the reliability, scalability, and quality of machine learning systems in a cloud environment. You will play a key part in building data validation and model evaluation pipelines that support end-to-end analytics and AI workflows. Working in a highly collaborative setup, you will partner with Data Science, Data Engineering, and Product teams to transform complex data challenges into structured, automated, and maintainable solutions. The environment is remote-first, dynamic, and centered on continuous improvement and technical excellence. You will also contribute to strengthening best practices in versioning, monitoring, and testing across data-driven systems. This position is ideal for a professional who combines strong analytical thinking with hands-on engineering skills in data science. Your work will directly impact the quality and reliability of data products used for decision-making.

• Design, build, and maintain data validation and model evaluation pipelines in cloud environments, primarily using AWS services.
• Develop automated and scalable workflows for integrating evaluation metrics and ensuring traceability and auditability of data processes.
• Modularize data science pipelines to enable reuse, maintainability, and efficient testing across different use cases.
• Collaborate closely with Data Science, Data Engineering, and Product teams to deliver end-to-end data-driven solutions.
• Implement and enforce best practices in versioning, logging, monitoring, and automated testing for data and ML pipelines.
• Contribute to the continuous improvement of data architecture, validation frameworks, and overall data quality processes.

• Bachelor’s degree in Engineering, Statistics, Mathematics, Systems Analysis, or a related quantitative field.
• Strong experience in data manipulation and statistical modeling using Python, SQL, and PySpark.
• Solid background in Data Science with experience solving complex analytical and data-related problems.
• Strong analytical thinking and structured problem-solving skills.
• Good communication skills and ability to work effectively in cross-functional and collaborative environments.
• Experience with cloud platforms, especially AWS (Glue, S3, SageMaker, Lambda, among others) is highly desirable.
• Familiarity with Agile methodologies is a plus.
• Experience applying LLMs in data science projects is a strong advantage.
• Exposure to optimization problems and algorithmic approaches is desirable.

• Fully remote work model.
• Opportunity to work on advanced data science and machine learning pipelines in cloud environments.
• Exposure to modern AWS-based data and ML services.
• Collaborative environment with strong interaction between data, engineering, and product teams.
• Focus on technical excellence, automation, and scalable architecture design.
• Continuous improvement culture with space to propose and implement new solutions.
• Experience working on real-world, high-impact data products.