Principal Data and Applied Scientist

We are looking for a Principal Data and Applied Scientist to join our team! As a member of the Enterprise Engineering and AI (EEAI) 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 meaningful 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.

Doctorate 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 Master’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 Bachelor’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) OR equivalent experience.

Other Requirements

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.

Preferred Qualifications

• Experience in Python, PySpark, and SQL.

• Exposure to ML development platforms such as Azure Machine Learning, Azure AI Foundry + Azure OpenAI.

• 6+ years of experience in data science, product/journey analytics, causal inference, and user behavioral modeling.

• Experience driving product improvements through data and insights.

• 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).

• Experience in ML development platforms such as Azure Machine Learning, Azure AI Foundry + Azure OpenAI.