Data Scientist: Energy System Modeler - PhD - Redmond

Come build community, explore your passions, and do your best work at Microsoft. This opportunity will allow you to bring your aspirations, talent, potential - and excitement for the journey ahead.

Data Scientists at Microsoft use machine learning, statistics, experiments, and more to build and improve great products while making business impact. The Microsoft Datacenter Energy Strategy and Partnerships Team identifies long term growth obstacles and develops global mitigation strategies, centralizing global functions to deliver consistency and scalability. This spans energy technology, resilience, commercial partnership, and business operations strategy.

The Energy System Modeler on the Microsoft Datacenter Energy Strategy Team will be responsible for conducting and managing electricity grid studies and analyses to ensure energy infrastructure investment, development, and reliability to support the global growth of Microsoft’s datacenters.   

You will demonstrate familiarity with a variety of grid models and studies, experience in conducting these studies and managing the development and outputs of such models, as well as identify business challenges and deliver insights needed to overcome them. You will develop a quantitative understanding of the energy infrastructure investments and policies needed to support Microsoft’s continued datacenter growth.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Please note this application is only for roles based in our Redmond, Washington office. For roles in other offices in the United States, please see our . 

Required Qualifications: 

• Doctorate (or currently pursuing) in Operational Research, Industrial System Engineering, Electrical Engineering, Computer Engineering, Statistics, Econometrics, Computer Science, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research).

Preferred Qualifications:

• 2+ years of experience in electricity grid modeling and optimization, power system planning and operation, energy markets and regulation. Both academic research and industry experience are considered.
• 2+ years of experience in developing and reviewing code using Python, Julia, or another contemporary high-level object-oriented programming language.
• Industrial experience, whether as an intern or in full-time roles, within energy industry consulting firms, ISO/RTOs, power system software vendors, or utility companies highly preferred.
• Experience with energy policy and regulatory analysis highly preferred.
• Understanding of datacenter industry or other large industrial customers.
• Ability to manage and prioritize multiple simultaneous projects with minimal direction.
• Growth mindset with advanced problem-solving skills to see the opportunity for grid models to inform energy infrastructure development.
• Experience with executive communication, adept at leveraging open communication and extensive stakeholder engagement to influence decisions and meet near and long-term goals.
• 1+ year(s) experience creating publications (e.g., patents, peer-reviewed academic papers).
• Experience or course work applying ML to a type of data and or used algorithms to conduct experiments on data.
• Proficiency in using one or more programming or scripting languages to work with data such as: Python, Perl, or C#.

Data Science IC3 - The typical base pay range for this role across the U.S. is USD $98,300 - $193,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $127,200 - $208,800 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Microsoft will accept applications, and process offers for these roles on an ongoing basis.

• Conduct analyses of energy system simulations and optimizations using state of the art commercial and open-source software, and communicate results in both reports/papers and presentations.
• Research and develop energy system models to support Microsoft datacenter growth by identifying and expanding capacity, lowering costs, and reducing carbon emissions. Research and evaluate grid models and analyses of global energy industry markets, infrastructure, and technologies.
• Leverage grid modeling and analysis to contribute to the development and maintenance of reliable and sustainable energy infrastructure to support datacenter operations and growth, identifying potential risks, efficiencies, and savings.
• Translate business needs into scopes of work for grid modeling and analyses. Develop assumptions, inputs, and scenarios for models to inform transmission capacity availability, transmission planning, generation capacity expansion, transmission reliability/availability, and clean energy procurement strategy.
• Interpret model results for cross-functional leadership. Propose business, investment, and operational recommendations informed by insights and backed by data. Work with energy regulatory policy leads to develop advocacy positions informed by grid analysis and company needs.
• Ensure stakeholder alignment and identify and mitigate risks for assigned projects. Manage change, negotiate deadlines and deliverables with stakeholders, prioritize work, and advise management on status, under guidance. Consider cross-functional inputs and balances competing business objectives. Communicate content status and performance to cross-functional teams. Serve as a point of contact to answer questions, provide feedback, and review work.
• Work with internal and external collaborators on topics including:
  • Demand flexibility
  • Reliability and resilience
  • Transmission expansion
  • Technology benefit and cost analysis
  • Projections of buildouts of generation, transmission, and energy storage
  • Electrification of transportation, building, and manufacturing