Senior Data Scientist

Posted Yesterday
Hiring Remotely in United States
Remote
120K-261K Annually
Senior level
Software • Quantum Computing • Metaverse • Infrastructure as a Service (IaaS)
The Role
Develop scalable data pipelines, statistical models, machine learning solutions, AI agents, dashboards, and decision-support tools for incentive compensation planning. Analyze large datasets, design quota and compensation models, evaluate business outcomes, ensure governance, and communicate recommendations to Finance, Engineering, product, sales, and executive stakeholders. The role also involves coding, debugging, automation, scenario modeling, and leading cross-functional analytical initiatives.
Summary Generated by Built In
Overview

 

 

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.


Responsibilities

 

 

The Senior Data Scientist is responsible for the following:

 

Business Understanding & Impact: 

  • 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.

 

Data Science: 

  • 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. 

 

Analytics & Evaluation:

  • 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.

 

Stakeholder Engagement:

  • 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.

 

Innovation & Continuous Improvement:

  • 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.

 

Governance and Compliance:   

  • Assesses programs for potential risks, verifying adherence to company policies and procedures when executing compensation practices.  
  • Identifies control measures and governance needs. 

 

 Coding and Debugging:

  • 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.

 

Other:

  • Embody our culture and values. 

Qualifications

 

 

Minimum Qualifications: 

  • 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.

 

 

Preferred Qualifications:

  • 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.

Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $160,200 - $261,000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay


This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.



Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Skills Required

  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or a related field plus 1 or more years of data science experience; or master's degree plus 3 or more years; or bachelor's degree plus 5 or more years; or equivalent experience.
  • Experience managing structured and unstructured data, applying statistical techniques, and reporting results.
  • Doctorate plus 3 or more years, master's degree plus 5 or more years, or bachelor's degree plus 7 or more years of data science experience, or equivalent experience.
  • 5 or more years of hands-on experience translating business requirements into data-driven solutions using machine learning algorithms such as classification, regression, clustering, or NLP.
  • 3 or more years of experience creating interactive dashboards and business insights using Power BI, Tableau, Looker, or equivalent tools.
  • 3 or more years of experience in business planning.
  • Clear communication and effective collaboration across cross-functional teams, including stakeholder and leadership communications.
  • 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.
  • Experience using Jupyter Notebooks, VS Code, or equivalent development environments for exploratory analysis and solution development.
  • Experience designing, building, or deploying agentic AI systems using autonomous agents, multi-agent orchestration, tool-use frameworks, or agent-based workflows.

Microsoft Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.

  • Fair & Transparent Compensation — Pay is presented as broadly competitive overall, with clear role/level/location variation and an emphasis on using posted ranges and band information for apples-to-apples comparisons.
  • Retirement Support — Retirement benefits are described as a standout, highlighted by a strong 401(k) match structure and immediate vesting, plus additional plan features for tax-advantaged saving.
  • Parental & Family Support — Family-oriented benefits are portrayed as a meaningful strength, with substantial paid parental leave and added supports like back-up care and adoption/surrogacy assistance.

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The Company
HQ: Redmond, WA
206,870 Employees
Year Founded: 1975

What We Do

At Microsoft, our mission is to empower every person and every organization on the planet to achieve more. Our mission is grounded in both the world in which we live and the future we strive to create. Today, we live in a mobile-first, cloud-first world, and the transformation we are driving across our businesses is designed to enable Microsoft and our customers to thrive in this world.

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