Senior Data Scientist

MICRON SEMICONDUCTOR ASIA OPERATIONS PTE LTD; Região Norte; On-site; BRL 180,000 - 320,000; Full time

Job summary

MICRON SEMICONDUCTOR ASIA OPERATIONS PTE LTD seeks a data science/ML professional to build, productionize, and operationalize AI solutions for semiconductor manufacturing. You will develop models, implement agentic AI features, and support decision workflows across test and production environments.

You should have strong Python expertise, experience with end-to-end ML development, and the ability to collaborate with cross-functional teams while delivering scalable, production-ready solutions.

Qualifications

• Bachelor's degree in a quantitative/technical field.
• Experience delivering data science/ML/AI solutions for complex problems.
• End-to-end ML development lifecycle including feature engineering and production integration.
• Experience collaborating with cross-functional teams on data-driven systems.

Responsibilities

• Build and productionize ML models to support predictive analytics for semiconductor operations.
• Develop multi-agent AI and LLM solutions and integrate RAG pipelines.
• Create scalable data pipelines and analytical code for high-volume manufacturing.
• Communicate complex results clearly to technical and non-technical stakeholders.

Skills

Python

ML/AI development

SQL

Data analysis

Education

Bachelor's degree in Computer Science

Tools

Docker

APIs

Cloud platforms (AWS/Azure/GCP)

Job description

Responsibilities and Tasks

• Product Quality (PQ) Predictive Solutions: Build and productionize machine learning models (classification and regression) to support predictive and prescriptive analytics across semiconductor test and manufacturing processes.
• Agentic AI and LLM Development:
• Contribute to the design and implementation of multi-agent systems for PQ workflows, including code generation, automated troubleshooting, and process optimization.
• Work with retrieval-augmented generation (RAG) pipelines: identify data sources, develop retrieval strategies, and improve context quality for LLM-based applications.
• Assist in implementing tool-using capabilities, function calling, and agent memory systems.
• Software Engineering and Productionalization:
• Develop maintainable code and analytical pipelines suitable for high-volume manufacturing environments.
• Optimize for performance, latency, and token efficiency.
• Collaborate with senior team members on testing, deployment, and monitoring.
• Communicate analytical insights, model behavior, and results clearly to technical and non-technical stakeholders
• Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements.
• Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work.
• Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements.
• Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work.

Required Qualifications & Skills

• Bachelor's degree in Computer Science, Data Science, Mathematics, Operations Research, Engineering, or a related quantitative/technical discipline.
• Experience developing data science, machine learning, or AI solutions for complex, data-intensive business problems.
• Experience with end-to-end machine learning development, including data preparation, feature engineering, model development, evaluation, optimization, and production integration.
• Experience working with multidisciplinary teams or integrating machine learning solutions into broader data, decision, or production systems.

Education / Experience

• Bachelor's degree in Computer Science, Data Science, Mathematics, Operations Research, Engineering, or a related quantitative/technical discipline.
• Experience developing data science, machine learning, or AI solutions for complex, data-intensive business problems.
• Experience with end-to-end machine learning development, including data preparation, feature engineering, model development, evaluation, optimization, and production integration.
• Experience working with multidisciplinary teams or integrating machine learning solutions into broader data, decision, or production systems.

Technical Skills

• Strong proficiency in Python for data analysis, machine learning, and model development.
• Strong foundation in machine learning, including supervised learning, feature engineering, model evaluation, representation learning, and model optimization.
• Experience using SQL and working with large-scale structured datasets.
• Experience developing scalable data and feature-engineering pipelines for machine learning applications.
• Experience deploying or integrating machine learning models into production systems and automated decision workflows.
• Familiarity with modern AI/ML techniques such as gradient boosting, graph neural networks, representation learning, Generative AI, RAG, or LLM-based systems
• Strong verbal and written communication skills, with the ability to explain complex analytical results clearly.
• Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business outcomes.

Preferred Qualifications

• Exposure to LLMs, agentic AI, or RAG-based solutions, through work experience, internships, academic work, or personal projects.
• Experience working with time-series, manufacturing/process data, imbalanced datasets, or concept drift.
• Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• Exposure to ETL/data pipelines, Docker, APIs, or web application frameworks.
• Coursework, research, or projects involving optimization, mathematical programming, or advanced statistical modeling.