Senior Data Scientist - IC5

Microsoft

18h

About The Position

With more than 45,000 employees and partners worldwide, the Customer Experience and Success (CE&S) organization is on a mission to empower customers to accelerate business value through differentiated customer experiences that leverage Microsoft’s products and services, ignited by our people and culture. We drive cross-company alignment and execution, ensuring that we consistently exceed customers’ expectations in every interaction, whether in-product, digital, or human-centered. CE&S is responsible for all up services across the company, including consulting, customer success, and support across Microsoft’s portfolio of solutions and products. Join CE&S and help us accelerate AI transformation for our customers and the world.
Within CE&S, the Customer Service & Support (CSS) organization builds trust and confidence for every person and organization through delivering a seamless support experience. In CSS, we are powered by Microsoft’s AI technology to help consumers, businesses, partners, and more, resolve their issues quickly and securely, helping prevent future problems from occurring and achieving more from their Microsoft investment.

We are looking for a Senior Data Scientist with to lead high-impact analyses focused on improving the operational efficiency of AI-powered features used by engineers in customer service workflows. This role requires strong expertise in causal inference and econometrics, including methods such as difference-in-differences, regression discontinuity designs, and randomized experiments. What makes this role distinctive is the opportunity to operate at the intersection of causal inference and modern AI systems. The ideal candidate will have familiarity with causal discovery methods (e.g., graphical models, structure learning) as well as experience evaluating LLM outputs along dimensions such as groundedness, robustness, and consistency. You will partner closely with cross-functional teams, including product, and finance, to ensure that both the impact and the quality of AI-driven features are measured, understood, and continuously improved.
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

• Masters Degree in Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 4+ years experience in data analysis and reporting, data science, business intelligence, or business and financial analysis OR Bachelors Degree in Statistics, Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 6+ years experience in data analysis and reporting, data science, business intelligence, or business and financial analysis OR equivalent experience.
• Ability to meet Microsoft, customer and / or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: 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

• Proven track record of using advanced statistical methods to assess the efficiency impact of change on established systems.
• Demonstrated ability to understand complex engineering workflows and consistently operate in alignment with organizational culture and values.
• Experience applying causal inference methods and experimental analysis to evaluate AI‑enabled features and LLM output quality.
• Proficient in SQL for data extraction and Python for building end‑to‑end analytical and modeling workflows.
• Ability to assess and build statistical models from very large data sets.

Responsibilities

• Develop and maintain a deep understanding of the end-to-end processes engineers use to resolve customer service cases.
• Apply causal inference techniques to estimate the impact of AI-enabled features using observational data; analyze randomized experiments where available; and evaluate the quality of LLM outputs.
• Critically assess and benchmark alternative models developed by partner teams, with a focus on both causal impact and output quality.
• Extract and transform data using SQL, and build analytical and modeling workflows in Python
• Embody our culture and values.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees