The Job

Senior Data Scientist

Technology, Data & Digital · Data, AI & Analytics · Data Science · Machine Learning · Artificial Intelligence

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In short

Microsoft seeks a Senior Data Scientist to shape the future of rewards and incentives using data-driven innovation. This role involves leveraging advanced analytics, AI, and predictive modeling to influence strategic decisions and optimize global incentive programs. You will work with cross-functional teams to build machine learning solutions and deliver insights that drive business impact.

Responsibilities

  • Define quota-setting strategy aligned with business, customer, and solution objectives.
  • Partner cross-functionally to identify and pursue opportunities for applying machine learning and other data-science methods to quota and incentive design.
  • Bridge Finance, Sales, Business Sales Operations, and Product teams through deep technical expertise.
  • Educate field managers and sales leaders on quota methodology, data inputs, and model mechanics.
  • Design, develop, and implement scalable methods, processes, and systems to consolidate and analyze large, diverse datasets.
  • Build and maintain data pipelines and automated processes to cleanse, integrate, and evaluate data from multiple sources.
  • Apply advanced statistical techniques and machine learning models to solve complex business problems.
  • Build AI agents that can deliver subject-relevant data and insights using natural language prompts.
  • 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 communication methods and delivery vehicles.
  • Evaluate performance and ensure alignment with business objectives.
  • Interpret and communicate insights clearly to technical and non-technical stakeholders.
  • Act as a trusted advisor to functional team members and org leadership.
  • Collaborate cross-functionally with internal and external stakeholders to define project roadmaps.
  • Contribute to the development of global tools and processes for communication and readiness analytics.
  • Identify opportunities for automation and process optimization.
  • Stay current with industry trends and emerging technologies in data science and incentive design.
  • Assess programs for potential risks, verifying adherence to company policies and procedures.
  • Write efficient, readable, and extensible code and models.
  • Lead project teams in gathering, integrating, and interpreting data from multiple sources to troubleshoot issues.
  • Generalize ML solutions into repeatable frameworks.
  • Enforce team standards for bias, privacy, and ethics.
  • Anticipate risks such as data leakage, bias/variance tradeoffs, and methodological limitations.
  • Drive best practices in model validation, implementation, and deployment.
  • Develop operational models that run reliably at scale.
  • Uncover new customer scenarios for transformative ML-driven solutions.
  • Oversee data acquisition and ensure datasets are properly formatted and accurately documented.
  • Use SQL, Python, and visualization tools to explore data.
  • Build data platforms from scratch across product lines.
  • Design data-science business solutions using established technologies, patterns, and practices.
  • Provide guidance on operationalizing models created by data scientists.
  • Identify new opportunities from data and processes it for general-purpose use.
  • Conduct thorough reviews of analytical techniques and processes.
  • Ensure clear alignment between selected models and business objectives.
  • Define and design feedback loops and evaluation methods to measure ongoing model impact.
  • Embody our culture and values.

Requirements

  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience OR Master's Degree AND 3+ years data-science experience OR Bachelor's Degree AND 5+ years data-science experience OR equivalent experience.
  • 5+ years of hands-on experience with cloud data platforms (e.g., Azure, AWS or Google etc.) required.
  • 5+ years of hands-on experience translating business requirements into data-driven solutions using ML algorithms required.
  • Effective communication skills and ability to collaborate across cross-functional teams.
  • Experience managing stakeholder and leader communications effectively.

Desired Qualifications

  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience OR Master's Degree AND 5+ years data-science experience OR Bachelor's Degree AND 7+ years data-science experience OR equivalent experience.
  • 2+ years of experience in PowerBI reporting and SSAS is a plus.
  • 2+ years of experience in business planning is plus.
  • Hands-on experience with cloud platforms and tools such as Azure Foundry, with a focus on developing and deploying AI models is a plus.
  • 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.

Benefits

  • The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year.
  • In San Francisco Bay area and New York City metropolitan area, the base pay range is USD $160,200 - $261,000 per year.
  • Certain roles may be eligible for benefits and other compensation.
  • Applications accepted on an ongoing basis until the position is filled.
#Data Science#Machine Learning#AI#Incentive Compensation#Sales Compensation#Analytics#Predictive Modeling#Cloud#Azure
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Company

Microsoft

Job Posted

2 weeks ago

Employment Type

Full Time

WorkMode

Remote

Experience Level

Senior

Locations

United States

Qualification

Doctoral, Master, Bachelor

Applicants

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