Senior Data Scientist

Microsoft•,

1d•$119,800 - $261,000

About The Position

Microsoft is a company where passionate innovators come to collaborate, envision what can be, and take their careers further. This is a world of more possibilities, more innovation, more openness, and the sky is the limit of thinking in a cloud-enabled world. Our sellers are key to how customers and partners understand Microsoft’s products and strategies, but how do we align the conversations of thousands of sellers with each other and with the company’s strategy? Making sure that the sellers are having the right conversations at the right time is key to the company’s success, and the Worldwide Incentive Compensation team connects strategy to seller behavior in one of the most important ways: by determining how sellers get paid. Worldwide Incentive Compensation (WWIC) is the team at Microsoft that is responsible for the design, implementation and operations related to the sales and incentive plans across all of Microsoft, impacting 40K+ employees. Our vision is to deliver effective, design-to-deployment incentive compensation that inspires sellers to maximize their success and rewards and enables sustainable growth, share, and customer success. This role blends deep technical expertise in data science with business acumen in incentive compensation plan design and implementation. You will partner with Plan design, Plan Implementation, Finance, Quota, Engineering and Business stakeholders to design solutions to drive efficiency, build machine learning solutions and AI agents, and deliver insights that improve compensation planning and implementation and drive operational efficiencies and seller outcomes. In addition, you’ll engage with diverse stakeholders, manage complex relationships, and drive innovation across the organization. We are looking for a Senior Data Scientist who is willing to work in a dynamic environment to solve real life day-to-day problems, leveraging data science techniques. You will enjoy and be successful in this role if you are curious and willing to challenge the status quo and come up with data-driven solutions to ambiguous problems. As a Senior Data Scientist, you will partner closely with data engineering, product, field, and Finance teams to turn large‑scale telemetry into decision-ready insights. You will help define compensable metrics, design quota models, evaluate outcomes, and ensure our quota distribution is explainable, reliable, and aligned to real business questions. Your work will directly influence product direction, customer success motions, and executive decision‑making. Microsoft’s mission is to empower every person and every organization on the planet to achieve more, and we’re dedicated to this mission across every aspect of our company. Our culture is centered on embracing a growth mindset and encouraging teams and leaders to bring their highly qualified contributions each day. Join us and help shape the future of the world.

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.
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 5+ 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 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience.
5+ years of hands-on experience translating business requirements into data-driven solutions using ML algorithms (e.g., classification, regression, clustering, NLP etc.).
3+ years of experience in creating interactive dashboards and business insights using Power BI, Tableau, Looker, or equivalent visualization tools.
3+ years of experience in business planning.
Communicates clearly and collaborates effectively across cross-functional teams. Experience managing stakeholder and leader communications effectively.
Hands-on expertise with Databricks, Azure Synapse, Snowflake, or similar cloud-based analytics platforms.
Proficiency with Python and data science libraries including Pandas, NumPy, PySpark, and Scikit-learn for data preparation, analysis, and modeling.
Experience using Jupyter Notebooks, VS Code, or equivalent development environments for exploratory analysis and solution development.
Experience designing, building, or deploying agentic AI systems — including autonomous agents, multi-agent orchestration, tool-use frameworks, or agent-based workflows using platforms such as LangChain, AutoGen, Semantic Kernel, or similar is a plus.

Nice To Haves

Experience designing, building, or deploying agentic AI systems — including autonomous agents, multi-agent orchestration, tool-use frameworks, or agent-based workflows using platforms such as LangChain, AutoGen, Semantic Kernel, or similar is a plus.

Responsibilities

Demonstrate proficient business acumen by aligning data science initiatives with strategic goals and proactively identifying opportunities for innovation and optimization.
Leverage understanding of incentive compensation design, levers, plans, metrics, roles, and governance processes. Develop deep expertise in Microsoft’s incentive compensation ecosystem, including compensation to support the development and evaluation of vehicles to drive operational efficiencies in plan design and implementation.
Present plan analyses, rationale, and cost implications, ensuring alignment with Microsoft’s software, services, and sales Go-to-Market strategies.
Collaborate with business teams to frame analytical questions, define hypotheses, and design experiments that inform product enhancements and client solutions.
Translate business objectives into analytical frameworks that help optimize compensation plan design and implementation decisions.
Present findings, recommendations, and tradeoffs to leadership, including plan design rationale, cost implications, risk assessments, and expected business outcomes.
Collaborate with business stakeholders to define hypotheses, evaluate alternative plan approaches, and quantify the impact of compensation changes before deployment.
Design, develop, and implement scalable methods, processes, and systems to consolidate and analyze large, diverse datasets—including unstructured “big data”—to generate actionable insights for business impact.
Build and maintain data pipelines and automated processes to cleanse, integrate, and evaluate data from multiple sources, ensuring high data quality and availability.
Apply advanced statistical techniques and machine learning models (e.g., classification, regression, NLP, forecasting) to solve complex business problems and drive measurable outcomes.
Develop AI agents and intelligent decision-support tools that enable Plan Design and Implementation teams to access compensation insights through natural language interactions.
Leverage Microsoft’s AI/ML stack (Azure Machine Learning, Azure Databricks, Azure Cognitive Services) to deploy scalable models.
Conduct scenario modeling and effective reviews of plan implementation processes
Evaluate performance and ensure alignment with business objectives.
Interpret and communicate insights clearly to technical and non-technical stakeholders, linking analytical findings to business objectives and recommending data-driven actions.
Act as a trusted advisor to functional team members and org leadership, providing insights that influence strategy and seller behavior.
Collaborate cross-functionally with internal and external stakeholders to define project roadmaps, evaluate model performance, and ensure continuous improvement through feedback loops.
Contribute to the development of global tools and processes for plan design and plan implementation analytics and insights.
Identify opportunities for automation and process optimization.
Stay current with industry trends and emerging technologies in data science and incentive design.
Assesses programs for potential risks, verifying adherence to company policies and procedures when executing compensation practices.
Identifies control measures and governance needs.
Writes efficient, readable, and extensible code and models spanning multiple features and solutions. Contributes to code and model reviews with actionable feedback, and maintains proficient capability in modeling, coding, and debugging techniques — including isolating and resolving errors and defects.
Leads project teams in gathering, integrating, and interpreting data from multiple sources to troubleshoot issues end-to-end. Provides feedback to product groups on non-optimized features and explores potential for new capabilities.
Embody our culture and values.