Data Scientist - Compete

Microsoft•Redmond, WA

13d

About The Position

Are you a data professional deeply interested in the current race in AI? Come join us! We are looking for a Data Scientist to support Compete. We help quantify how Microsoft products are performing relative to the broader marketplace e.g. market share across a variety of metrics. We use a wide combination of data sources (1P, 3P, public, surveys, panels, etc) and science models to produce our estimates. As a business facing team, interest and ability to connect product and strategy hypotheses back to data and qualitative factors is central to the role. AI is a big focus, both as a competitive space (e.g. Copilot, ChatGPT, Gemini, Claude, etc) and because we are actively integrating AI into our daily workflows. Join over 150 data scientists on the broader horizontal IDEAs team where data science, engineering, and PM work together to support multiple business and product verticals at scale! In this role you will both support stakeholders directly and work with the broader IDEAs team to scale your solutions across Microsoft. We play a crucial role in supporting Microsoft 365 and the Experiences + Devices group (E+D), both of which are central to the Company's mission to empower individuals and organizations to achieve more. Our objective is to foster a data-informed culture by equipping the Experiences + Devices group with actionable insights to guide their decisions. This initiative represents a significant opportunity to deliver impactful information that will improve operational efficiency, drive empowerment, and support Microsoft’s success in the evolving AI landscape. 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

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 Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience
OR Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience
OR equivalent experience.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Nice To Haves

Longer job experience than the minimum required
Experience writing SQL queries
Experience supporting software products and metrics (e.g. active usage)
Experience directly supporting business stakeholders
Experience working with product and engineering to scale your solutions

Responsibilities

Business Understanding, Impact, and Management. Understands problems facing projects. Able to leverage knowledge of data science to uncover important factors that can influence outcomes. Describes the primary objectives of the team from a business perspective. Collaborates with internal cross-functional stakeholders to understand business needs. Produces a project plan to specify necessary steps required for completion. Assesses current situation for resources, risks, contingencies, requirements, assumptions, and constraints. Engages business stakeholders to capture and shape their thinking on data-driven methods. Leads customer conversations to understand, define, and solve business problems. Influences stakeholders by effectively making compelling cases through storytelling, visualizations, and other influencing tools. Exemplifies and enforces team standards related to bias, privacy, and ethics.
Data Preparation and Understanding. Acquires data necessary for successful completion of the project plan. Proactively detects changes and communicates to senior leads. Develops useable data sets for modeling purposes. Contributes to ethics and privacy policies related to collecting and preparing data by providing updates and suggestions around internal best practices. Contributes to data integrity/cleanliness conversations with customers.
Coding and Debugging. Writes efficient, readable, extensible code from scratch that spans multiple features/solutions. Develops technical expertise in proper modeling, coding, and/or debugging techniques. Understands the causes of common defects and uses best practices in preventing them from occurring. Collaborates with other teams and leverages best practices from those teams into work of their own team. Mentors and guides less experienced scientists in better understanding coding and debugging best practices.
Customer/Partner Orientation. Applies a customer-oriented focus by understanding customer needs and perspectives. Builds trust with customers by leveraging interpretability and knowledge of Microsoft products and solutions. Helps drive realistic customer expectations, including information about the limitations of their data.
Industry and Research Knowledge / Opportunity Identification. Uses business knowledge and technical expertise to provide feedback to the engineering team to identify potential future business opportunities. Develops an understanding of work being done across teams to propose potential collaboration efforts. Coaches and provides support to execute strategy. Leverages capabilities within existing systems.
Modeling and Statistical Analysis. Leverages knowledge of machine learning solutions and individual algorithms to identify the best approach to complete objectives. Understands modeling techniques and selects the correct approach to prepare data, train and optimize the model, and evaluate the output for statistical and business significance. Breaks down complex statistics and machine learning topics into manageable topics to explain to customers.

Stand Out From the Crowd

Upload your resume and get instant feedback on how well it matches this job.

Upload and Match Resume