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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, Data Presentation, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, SQL Databases, Feature Engineering, Large Language Models, Model Validation, Agentic-AI, Matplotlib, Information Technology, Plotly
- **Published:** October 10, 2026
- **Apply:** https://dejobs.org/x/x/9ABF66C5E3F444D7B0983787BB335C12/job/

## 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

* 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.