Senior Data and Applied Scientist

Overview With the rapid acceleration of AI and the need to deliver trustworthy, high-performing models, Microsoft's Commercial Business & AI (CEAI) Data Science and Applied AI team is driving innovation at scale! Our mission is to advance AI capabilities through rigorous evaluations, fine-tuning, and large-scale experimentation to create intelligent, personalized experiences for customers worldwide. The CEAI Data Science and Applied AI team is seeking passionate AI practitioners and data scientists to join agile, cross-functional teams working on cutting-edge model evaluation frameworks, optimization pipelines, and experimentation platforms that power Microsoft's AI ecosystem. We are looking for a Senior Data and Applied Scientist to join our team! As a member of the Commercial Business & AI (CEAI) Data Science and Applied AI organization at Microsoft, you will help us accelerate the company's own AI transformation. You will have the opportunity to partner directly with the engineering and product management groups responsible for managing the Dynamics 365 applications that power Microsoft's sales, marketing, and support platforms. You will apply advanced analytics, statistical modeling, machine learning and GenAI tools to uncover insights, drive action and deliver innovative solutions for complex business challenges. This role offers the opportunity to: Collaborate across a diverse team of data scientists, engineers, and product managers. Deepen your expertise in the evolving AI and ML landscape. Drive impact for thousands of Microsoft sales, marketing and support platform users. 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 Work with key stakeholders to understand the underlying business needs and formulate the needs into discrete, manageable problems with well-defined measurable objectives and outcomes. Transform formulated problems into implementation plans by defining success metrics, applying/creating the appropriate methods, algorithms, and tools, as well as delivering statistically valid and reliable results. Write robust, reusable, and extensible code to support analysis and modeling. Develop new ML or GenAI based models using advanced statistical and ML techniques. Lead the evaluation of various GenAI based solutions, diagnosing issues and identifying root causes to support potential fine-tuning or reinforcement learning based fixes. Use AI-powered tools in your daily work to accelerate coding, analysis, and other tasks. Qualifications Required/minimum qualifications Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ 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 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience. Preferred Qualifications 4+ years of experience in data science, product/journey analytics, causal inference, and user behavioral modeling. Experience driving product improvements through data and insights. Experience in Python, R, SQL, KQL, PySpark, and modern analytics frameworks. Experience designing experiments, defining standardized metrics, performing causal analyses, and delivering behavior-driven insights. Experience with learning platforms and/or learner competency and skill modeling (e.g., proficiency, mastery, and skill signals). Experience levering AI to deliver accelerate time to insight and depth of insights Experience with large-scale enterprise data platforms (e.g., Fabric, Synapse, ADX, Delta Lake, ADF, Databricks, Snowflake). Exposure to ML development platforms such as Azure Machine Learning, Azure AI Foundry + Azure OpenAI. Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $160,200 - $261,000 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.