Principal Data Scientist

May 7, 2026

Other Jobs To Apply

<div class="container-3Gm1a">Overview Microsoft is a company where passionate innovators come to collaborate, envision what can be, and take their careers further. This is a world of more possibilities, more innovation, more openness, and the sky is the limit of thinking in a cloud-enabled world.We are looking for a Principal Data Scientist who is willing to work in a dynamic environment to solve real life day-to-day problems, leveraging data science techniques. You will enjoy and be successful in this role if you are curious and willing to challenge the status quo and come up with data-driven solutions to ambiguous problems.As a Principal Data Scientist, you will partner closely with data engineering, product, field, and Finance teams to turn large‑scale telemetry into decision-ready insights. You will help define compensable metrics, design quota models, evaluate outcomes, and ensure our quota distribution is explainable, reliable, and aligned to real business questions. Your work will directly influence product direction, customer success motions, and executive decision‑making.Microsoft’s mission is to empower every person and every organization on the planet to achieve more, and we’re dedicated to this mission across every aspect of our company. Our culture is centered on embracing a growth mindset and encouraging teams and leaders to bring their highly qualified contributions each day. Join us and help shape the future of the world. Responsibilities The Principal Data Scientist is responsible for the following:Business Management: <ul style="margin-bottom: 0.0in; margin-top: 0.0px;"><li style="line-height: normal; background-color: white; margin: 0in 0in 0in 0px;">Defines quota-setting strategy aligned with business, customer, and solution objectives. Partners cross-functionally to identify and pursue opportunities for applying machine learning and other data-science methods to quota and incentive design.</li><li style="line-height: normal; background-color: white; margin: 0in 0in 0in 0px;">Bridges Finance, Sales, Business Sales Operations, and Product teams through deep technical expertise. Drives cross-discipline collaboration and leads efforts to refine intellectual property definitions and methodology improvements.</li><li style="line-height: normal; background-color: white; margin: 0in 0in 0in 0px;">Educates field managers and sales leaders on quota methodology, data inputs, and model mechanics through roadshows, workshops, and ongoing enablement — ensuring transparency and building trust in the quota-setting process.</li></ul>Business Understanding and Impact<ul style="margin-bottom: 0.0in; margin-top: 0.0px;"><li style="margin: 0in 0in 0in 0px; line-height: normal; background-color: white;">Applies deep domain expertise to analyze challenges across product lines, identifying and mitigating risks that could influence quota outcomes.</li><li style="margin: 0in 0in 0in 0px; line-height: normal; background-color: white;">Partners with business stakeholders to shape strategy, recommend improvements, and surface opportunities to extend existing work into new contexts. Establishes and promotes standards and best practices across teams.</li></ul>Coding and Debugging: <ul style="margin-bottom: 0.0in; margin-top: 0.0px;"><li style="line-height: normal; background-color: white; margin: 0in 0in 0in 0px;">Writes efficient, readable, and extensible code and models spanning multiple features and solutions. Contributes to code and model reviews with actionable feedback, and maintains strong expertise in modeling, coding, and debugging techniques — including isolating and resolving errors and defects.</li><li style="line-height: normal; background-color: white; margin: 0in 0in 0in 0px;">Leads project teams in gathering, integrating, and interpreting data from multiple sources to troubleshoot issues end-to-end. Provides feedback to product groups on non-optimized features and explores potential for new capabilities.</li><li style="line-height: normal; background-color: white; margin: 0in 0in 8pt 0px;">Brings expert-level proficiency in big-data and ML engineering tools and practices, including Hadoop, Apache Spark, CI/CD, Docker, Delta Lake, MLflow, Azure ML, and REST API development.</li></ul>Customer/Partner Orientation<ul style="margin-bottom: 0.0in; margin-top: 0.0px;"><li style="margin: 0in 0in 0in 0px; line-height: normal; background-color: white;">Maintains a customer-first mindset — understanding stakeholder needs, validating their perspectives, and serving as a trusted advisor within the broader organizational context.</li><li style="margin: 0in 0in 0in 0px; line-height: normal; background-color: white;">Adds strategic value by connecting business understanding, product functionality, data sources, and methodology expertise to reframe problems and deliver actionable insights. Leads customer discussions and offers pragmatic solutions that account for real-world data limitations.</li></ul>Modeling and Statistical Analysis:<ul style="margin-top: 12.0pt; margin-bottom: 0.25in;"><li style="margin: 12pt 0in 0.25in 0px; line-height: normal;">Generalizes ML solutions into repeatable frameworks — modules, packages, and general-purpose tools — for broader team reuse. Enforces team standards for bias, privacy, and ethics. Reviews teammates' model methodology and performance, recommending improvements where appropriate.</li><li style="margin: 12pt 0in 0.25in 0px; line-height: normal;">Anticipates risks such as data leakage, bias/variance tradeoffs, and methodological limitations, guiding teammates toward sound solutions. Drives best practices in model validation, implementation, and deployment. Develops operational models that run reliably at scale. </li><li style="margin: 12pt 0in 0.25in 0px; line-height: normal;">Partners cross-functionally to identify opportunities for ML and predictive analysis. Uncovers new customer scenarios for transformative ML-driven solutions while incorporating AI ethics best practices. Maintains deep, current expertise in emerging AI/ML methodologies.</li></ul>Data Preparation and Understanding: <ul style="margin-bottom: 0.0in; margin-top: 0.0px;"><li style="line-height: normal; background-color: white; margin: 0in 0in 0in 0px;">Oversees data acquisition and ensures datasets are properly formatted and accurately documented. Uses SQL, Python, and visualization tools to explore data — analyzing distributions, attribute relationships, sub-population properties, and statistical summaries.</li><li style="line-height: normal; background-color: white; margin: 0in 0in 0in 0px;">Builds data platforms from scratch across product lines. Designs data-science business solutions using established technologies, patterns, and practices. Provides guidance on operationalizing models created by data scientists.</li><li style="line-height: normal; background-color: white; margin: 0in 0in 8pt 0px;">Identifies new opportunities from data and processes it for general-purpose use. Contributes to thought leadership and IP on data acquisition best practices. Leads resolution of data-integrity issues.</li></ul><h4 style="margin: 4pt 0in 2pt; line-height: 115%; color: rgb(15, 71, 97); font-weight: normal; font-style: italic;">Evaluating for Insights and Impact: </h4><ul style="margin-bottom: 0.0in; margin-top: 0.0px;" type="disc"><li style="margin-bottom: 0in; line-height: normal; margin-top: 0in; margin-right: 0in;">Conducts thorough reviews of analytical techniques and processes, highlighting gaps or areas needing reexamination. Uses assessment findings to determine next steps — deployment, further iteration, or new project directions.</li><li style="margin-bottom: 0in; line-height: normal; margin-top: 0in; margin-right: 0in;">Ensures clear alignment between selected models and business objectives, validating that model outputs drive meaningful outcomes.</li><li style="margin-bottom: 0in; line-height: normal; margin-top: 0in; margin-right: 0in;">Defines and designs feedback loops and evaluation methods to measure ongoing model impact.</li></ul>Coach and Mentoring: <ul style="margin-bottom: 0.0in; margin-top: 0.0px;"><li style="line-height: normal; background-color: white; margin: 0in 0in 0in 0px;">Mentors engineers on data cleaning, analysis best practices, and ethical data handling. Identifies gaps in existing datasets and drives onboarding of new sources, including third-party data. Champions ethics and privacy discussions, integrating industry-wide insights to influence internal processes and decision-making.</li><li style="line-height: normal; background-color: white; margin: 0in 0in 0in 0px;">Maintains strong proficiency in the Microsoft AI/ML toolset (Azure Machine Learning, Azure Cognitive Services, Azure Databricks). Translates complex statistical and ML concepts into accessible explanations for customers and stakeholders.</li></ul>Other<ul style="margin-top: 0.0in; margin-bottom: 0.0in;" type="disc"><li style="margin-top: 0in; margin-right: 0in; margin-bottom: 8pt; line-height: 115%;">Embody our <a href="https://careers.microsoft.com/us/en/culture">culture</a> and <a href="https://www.microsoft.com/en-us/about/corporate-values">values</a>. </li></ul> Qualifications <ul><li style="line-height: normal;">Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)</li><li style="list-style-type: none;"><ul style="margin-bottom:0.0in;margin-top:0.0px"><li style="margin: 0in 0in 0in 0px; line-height: normal;">OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)</li><li style="margin: 0in 0in 0in 0px; line-height: normal;">OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)</li><li style="margin: 0in 0in 0in 0px; line-height: normal;">OR equivalent experience.</li></ul></li></ul>Additional or preferred qualifications: <ul style="margin-top:0.0in;margin-bottom:0.0in"><li style="margin: 0in 0in 0in 0px; background-color: white;">Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) <ul style="margin-top:0.0in;margin-bottom:0.0in"><li style="margin: 0in 0in 0in 0px; background-color: white;">OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) </li><li style="margin: 0in 0in 0in 0px; background-color: white;">OR equivalent experience.</li></ul></li></ul><ul style="margin-top:0.0in;margin-bottom:0.0in"><li style="margin: 0in 0in 0in 0px; background-color: white;">10+ years of hands-on experience with cloud data platforms (e.g., Azure, AWS or Google etc.).</li><li style="margin: 0in 0in 0in 0px; background-color: white;">10+ years of programming experience in Python, SQL Server, and PySpark, including understanding and maintaining scalable data pipelines and machine learning models.</li><li style="margin: 0in 0in 0in 0px; background-color: white;">10+ years of hands-on experience translating business requirements into data-driven solutions using ML algorithms (e.g., classification, regression, clustering, NLP etc.).</li><li style="margin: 0in 0in 0in 0px; background-color: white;">2+ year of experience in PowerBI reporting and SSAS is a plus</li><li style="margin: 0in 0in 0in 0px; background-color: white;">2+ year of experience in business planning is plus. </li><li style="margin: 0in 0in 0in 0px; background-color: white;">Strong communication skills and ability to collaborate across cross-functional teams. </li><li style="margin: 0in 0in 0in 0px; background-color: white;">Experience managing stakeholder and leader communications effectively.</li><li style="margin: 0in 0in 0in 0px; background-color: white;">Experience in quota modeling, incentive compensation, or sales analytics and forecast is a plus.</li><li style="margin: 0in 0in 0in 0px; background-color: white;">Proven ability to mentor junior data scientists and lead end-to-end ML lifecycle projects.</li><li style="margin: 0in 0in 0in 0px; background-color: white;">Hands-on experience with cloud platforms and tools such as Azure Synapse and Azure Foundry, with a focus on developing and deploying AI models is a plus. </li><li style="margin: 0in 0in 0in 0px; background-color: white;">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.</li></ul> Data Science IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 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 $188,000 - $304,200 per year. Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: <a href="https://careers.microsoft.com/us/en/us-corporate-pay">https://careers.microsoft.com/us/en/us-corporate-pay</a> This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. <hr> 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 <a href="https://careers.microsoft.com/v2/global/en/accessibility.html">requesting accommodations.</a> </div>

Back to blog

DISCLAIMER

Other Jobs To Apply