Senior Data Scientist - FDE

Microsoft•Redmond, WA

10h•$119,800 - $261,000

About The Position

In the Microsoft Frontier Company Engineering team, you won’t just build software; you’ll deliver real outcomes for some of the world’s most complex organizations. We are a global team of world-class engineers who have been working in a Forward Deployed Engineering (FDE) model for more than a decade, embedding directly within customer teams to solve their toughest challenges, side-by-side, and shipping production-ready solutions in days, not months. As a Senior Data Scientist, you will help transform how organizations use data, developing models, running experiments, and driving evidence-based decisions that have measurable business impact. You’ll work in small, multidisciplinary crews alongside engineers, product managers, and domain experts, owning the full lifecycle from data discovery through to deployed solutions. Our work is powered by AI, applying the mindset and tooling across the entire development lifecycle to move from idea to production in days while maintaining the highest standards of security, quality, and trust. This role offers the opportunity to: Work with messy, real-world datasets and turn them into scalable, production-ready solutions. Run experiments that directly influence business strategy and customer outcomes. Collaborate with leading global organizations across industries. Apply the latest advancements in AI and data science to solve problems at scale. 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.

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
Microsoft is unable to sponsor a work visa for this role due to the nature of the role’s job duties.

Nice To Haves

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 6+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
Experience partnering directly with customers or internal stakeholders to deliver solutions end-to-end.

Responsibilities

Oversee acquisition of the data sets necessary for your project delivery and ensure data is properly formatted and described.
Address any gaps in current data sets, and drive ethics and privacy discussions around data collection and preparation.
Evaluate your team’s models using metrics tied to genuine business outcomes and recommend improvements as necessary, drive best practices for models, and develop operational models that run at scale.
Conduct thorough reviews of data analysis and modeling techniques and identify and invent new evaluation methods.
Research and maintain a deep knowledge of the industry, including trends and technologies, so that you can identify strategy opportunities and contribute to thought leadership in best practices.
Write extensible code that spans multiple features and develops expertise in proper debugging techniques.
Define business, customer, and solution strategy goals, and partner with other teams to identify and explore new opportunities.
Commit to a customer-oriented focus by acknowledging their needs and offering customer pragmatic solutions that align with their data capabilities.
Coach engineers and cross-disciplinary partners in data science best practices and scale knowledge within the cross discipline team.