Design secure Azure AI and cloud solutions, leading architecture engagements, proofs of concept, pilots, and production adoption for customer applications and agents.
About this role
On Microsoft Frontier Company Engineering's forward-deployed teams, the Principal Data Scientist works with engineers, product managers and domain experts to help organizations solve problems with data, from discovery to production. The role oversees data acquisition and preparation, explores data with SQL and Python, and develops, validates and evaluates statistical and machine-learning models. It builds data platforms and reusable ML frameworks, guides model deployment at scale, resolves data-integrity issues, and applies practices for bias, privacy and ethics. It also reviews code and model performance, devises evaluation approaches, explains findings to customers and coaches engineers. Named technologies include Hadoop, Apache Spark, CI/CD, Docker, Delta Lake, MLflow, AML and REST APIs. Applicants need a bachelor's degree in data science or another listed discipline plus 10+ years of data-science experience, a master's degree plus 7+ years, or a doctorate plus 5+ years; equivalent experience is accepted. Experience includes managing structured and unstructured data, applying statistical techniques and reporting results.
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