Senior Data Scientist at Microsoft in Charlotte, NC

Overview
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.
In the Customer Service & Support (CSS) team, we are looking for a Data Scientist with a passion for leveraging advanced analytics, statistical methodologies, and machine learning to drive business outcomes. In this role, you will design experiments, develop predictive and analytical models, and generate actionable insights from complex datasets to inform decision-making. You will partner closely with engineering, product, and business stakeholders to identify opportunities, measure impact, and improve operational effectiveness through data-driven solutions. This opportunity will allow you to deepen your expertise in data science, artificial intelligence, experimentation, and advanced analytics while contributing to Microsoft's customer success mission.
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.

Responsibilities
Design and analyze experiments, including A/B tests and observational studies, to measure business impact and support decision-making.
Apply causal inference methodologies to evaluate outcomes and identify performance improvement opportunities.
Develop, validate, and deploy machine learning models for prediction, classification, and analytical use cases.
Apply statistical methods to quantify uncertainty, evaluate results, and ensure analytical rigor.
Partner with engineering and business teams to define metrics, establish measurement frameworks, and improve data collection processes.
Evaluate AI and LLM-based solutions using structured testing methodologies, performance metrics, and analytical frameworks.
Communicate findings and recommendations through compelling visualizations, presentations, and data-driven storytelling.
Drive adoption of advanced analytics, experimentation, and machine learning bestpractices across the organization.

Qualifications
Required Qualifications:
Bachelor's Degree in Computer Science, Information Technology (IT), or related field AND 5+ years of technical support, technical consulting, data science, analytics, or information technology experience
o OR 7+ years of years of technical support, technical consulting, data science, analytics, or information technology experience
o OR equivalent experience.
Additional Required Qualifications:
Deep expertise in causal inference — experimental design and observational causal methods.
Statistical foundation — hypothesis testing, regression, Bayesian and frequentist methods, uncertainty quantification.
Solid machine learning skills — feature engineering, model selection, evaluation, and validation.
Experience evaluating LLMs and/or AI agents — designing offline/online evaluations, defining quality metrics, and measuring model behavior.
Data storytelling — crafting compelling data stories through enhanced visualizations in Python (e.g., matplotlib, seaborn, plotly) or other tools.
Proficiency in Python or R and SQL.
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.

Technical Support Engineering IC5 - The typical base pay range for this role across the U.S. is USD $106,400 - $203,600 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 $137,600 - $222,600 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.
Insights from previous hires
Top skills: Analytics, Algorithms, Amazon Web Services (AWS), Academic Writing, Science, SQL, Python, Machine Learning, Linux, Java
Common previous titles: Scientist, Senior Data Scientist, Data Scientist, Consultant, Cloud Solution Architect, Tech Support Engineer, Learning Manager, Senior Consultant, Software Engineer 2, Software Engineer