Data Scientist

Job Overview

As a Staff Data Scientist in Finance Systems Transformation at Micron, you will build and develop customized AI conversational agents, advanced analytical models, and predictive solutions that support decision‑making across Finance. You will apply mathematics, statistics, machine learning, and data engineering to build scalable solutions on Snowflake-based finance data, improving prediction accuracy, deviation assessment, and scenario planning. This role focuses on delivering high‑impact, production‑grade solutions that transform Finance operations.

• Lead the development of predictive models for finance use cases, including forecasting (revenue, expenses, cost drivers), variance analysis (actuals vs. plan), and scenario modeling.
• 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, designing agent‑based workflows, prompt design, evaluation frameworks, and performance testing.
• Partner closely with Finance business stakeholders, Data Engineering, and UX teams to translate business problems into data science solutions, define success metrics, validate model performance, and drive adoption of analytics and AI capabilities.
• Build and optimize data pipelines and modeling workflows to cleanse, 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 productization.

• 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, Num Py, and scikit‑learn, and experience in Snowflake, Streamlit, and modern AI/ML development environments.
• Experience 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, and 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.

• Advanced degree (Master’s or Ph.D.) in a quantitative discipline.
• Experience applying advanced machine learning, time‑series modeling, optimization, or AI techniques to Finance data, workflows, and business needs.
• Hands‑on experience developing, deploying, and monitoring conversational AI agents or LLM‑based solutions in Snowflake, cloud, or similar enterprise data environments.
• 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 dashboards or lightweight front‑end experiences that improve how Finance users interact with models and insights.

US base salary range: $ – $ per year. Additional compensation may include benefits, bonuses, and equity.

Micron offers a range of medical, dental, and vision plans, income‑protection programs, paid family leave, robust paid time‑off, and paid holidays. For more information, please see the Benefits Guide posted on

Micron is proud to be an equal‑opportunity workplace and is an affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, age, national origin, citizenship status, disability, protected veteran status, gender identity, or any other factor protected by applicable federal, state, or local laws.