Data Scientist

Position: Staff Data Scientist
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.

Responsibilities include, but not limited to:

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

Minimum Qualifications:

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, 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.

Preferred Qualifications:

Advanced degree (Master’s or PhD) in Data Science, Computer Science, Statistics, Mathematics,…