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# Senior Data Scientist

- **Company:** Microsoft
- **Location:** Redmond, WA, United States
- **Experience:** Expert
- **Salary:** $106,400.0 - $203,600.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Data Analysis, Microsoft Online Services, Cascading Style Sheets (CSS), Data Presentation, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, SQL Databases, Feature Engineering, Large Language Models, Model Validation, Matplotlib, Information Technology, Plotly
- **Published:** August 5, 2026
- **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17841605?backUrl=%2Fcareer%2F17841605%2FSenior-Data-Scientist-Washington-Redmond

## About the Role

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.

## Description

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.


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