Staff Data Scientist

Micron Technology • Austin, TX

3d • $123,000 - $290,000

About The Position

Our vision is to transform how the world uses information to enrich life for all. Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. As a Staff Data Scientist in Finance Systems Transformation at Micron, you will help build and develop customized AI conversational agents. You will also develop advanced analytical models and predictive solutions that support decision-making across Finance. You will apply your knowledge in mathematics, statistics, machine learning, and data engineering to build scalable solutions on Snowflake-based finance data. These solutions improve prediction accuracy, deviation assessment, and scenario planning. This role is passionate about delivering high-impact, production-grade solutions that transform Finance operations. It emphasizes instructed dialogue systems, predictive modeling, intelligent automation, and new agent-based architectures. You will collaborate with Data Scientists, Data Engineers, Finance Business Users, and UX teams to find questions and problems. You will create solutions for budgeting, income statement, manufacturing expense data domains, and more. In this role, you will write software programs, algorithms, models, and agent instructions. Your work will cleanse, combine, analyze, and assess large datasets from various sources. There are many chances to explore data and develop new solutions that turn finance business logic into code and smart agent actions.

Requirements

• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Finance, Economics, or a related quantitative field, plus 5+ years of experience in data science, machine learning, or advanced analytics roles.
• Strong proficiency in Python and SQL, with hands-on experience developing, testing, and deploying predictive or statistical models on large, complex datasets.
• Working knowledge of core data science and AI/ML tools, including Python libraries such as pandas, NumPy, and scikit-learn, with hands-on experience in Snowflake, Streamlit, and modern AI/ML development environments.
• Experience working with Finance-related data, workflows, and business needs, including corporate finance, P&L, and manufacturing cost data, as well as forecasting, variance analysis, scenario planning, actuals-to-forecast reconciliation, or financial waterfall reporting.
• Experience partnering with Finance stakeholders and cross-functional teams to deliver scalable, user-adopted solutions, and providing technical leadership or mentorship to data scientists and analysts.

Nice To Haves

• Advanced degree (Master’s or PhD) in Data Science, Computer Science, Statistics, Mathematics, Operations Research, Finance, Economics, or a related quantitative discipline.
• Experience applying advanced machine learning, time series modeling, optimization, or AI techniques to Finance-related data, workflows, and business needs, including corporate finance, P&L, manufacturing cost data, forecasting, scenario modeling, driver analysis, or decision support.
• Hands-on experience developing, deploying, and monitoring conversational AI agents or LLM-based solutions in Snowflake, cloud, or similar enterprise data environments, including prompt/instruction design, evaluation, and performance optimization.
• Experience translating finance business logic into production-grade analytical applications, model features, prompts, rules, or agent workflows that support scalable decision-making.
• Experience with data visualization and basic UI development, including creating intuitive dashboards, analytical interfaces, or lightweight front-end experiences that improve how Finance users interact with models, insights, and AI-enabled solutions.

Responsibilities

• Lead the development of predictive models for finance use cases, including: Forecasting (revenue, expenses, cost drivers) Variance analysis (actuals vs. plan, drivers of deviation) Scenario modeling and sensitivity analysis to support business planning
• Build and implement scalable, production-grade analytical models that integrate with enterprise finance systems and data platforms
• Develop, test, and deploy intelligent agents in a Snowflake environment, including: Agent-based workflows for finance analytics use cases Prompt design, evaluation frameworks, and performance testing Monitoring and continuous improvement of agent outputs
• Partner closely with Finance business stakeholders, Data Engineering, and UX teams to: Translate business problems into data science solutions Define success metrics and validate model performance Drive adoption of analytics and AI capabilities
• Build and optimize data pipelines and modeling workflows to clean, combine, and analyze vast, detailed data compilations from multiple sources
• Lead exploratory analysis and prototype development to identify new opportunities for automation, insight generation, and decision support
• Provide technical leadership and mentorship to junior data scientists, setting best practices for modeling, experimentation, and product ionization

Benefits

• Choice of medical, dental and vision plans
• Benefit programs that help protect your income if you are unable to work due to illness or injury
• Paid family leave
• Robust paid time-off program
• Paid holidays

What This Job Offers

• Job Type: Full-time
• Career Level: Senior