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Microsoft Principal Data Applied Sciences Manager 
United States, Washington 
453803990

25.06.2024

and associated experiences to Teams, Skype andthird party

and Applied Sciences Managertobuild highly scalableAI offeringsusing latest technologies in a dynamic and agile environment and have opportunities to

Required Qualifications:

  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
    • OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics, predictive analytics, research)
    • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
    • OR equivalent experience
  • 1+ year(s) people management experience
  • 6+ years of experience developing and deploying end-to-end ML/AI systems. Skills include working with structured and unstructured data, data processing at scale, feature engineering, and model operationalization
  • 4+ years of experience with design, implementation, debugging and testing of complex distributed services
  • 3+ years of experience working on Machine Learning models specifically with Natural language-based models, vector databases and graph databases

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:

  • a track recordof managing both technical and non-technical stakeholders, adept at resolving intricate business and technical challenges
  • Demonstrated experience with software engineering principles, parallel and distributed computing, statistics, machine learning, and cloud technologies like Azure, AWS, or Google Cloud is highly valued
  • Doctorate in Computer Science, Mathematics, Physics, Electrical Engineering, or equivalent
  • 9+ years of experience in Machine Learning
  • 5+ years using ML tools likePytorchand TensorFlow
  • Practical experience developing applications using prompt engineering, fine tuning, OpenAIor Azure Open AI APIs
  • System development skills, with a long-range system view that leverages development ranging from rapid research prototypes to carefully architected complex systems

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:Microsoft will accept applications for the role until July 5th, 2024.

Responsibilities

, fostersexcellence, and values diverse perspectives and authenticity.


Business Understanding and Technical Oversight:

  • Lead data science projects or teams to meet business requirements and deliver results
  • Define and communicate technical direction and strategy for projects and teams, considering project goals, industry trends, and technical context
  • Offer technical guidance, recommend best practices, andfacilitateteam consensus on practices
  • Ensure project deliverables meet quality standards by setting clear expectations and overseeing implementation

Data Preparationand Evaluation

  • Conduct thorough exploratory data analysis on complex datasets toidentifypatterns and generate relevant hypotheses, employing statistical techniques like hypothesis testing and regression analysis
  • Ensure data quality and reliability by addressing issues such as data cleaning, preprocessing, missing data, outliers, and anomalies
  • Collaborate with stakeholders toestablishprojectobjectivesand design evaluation methods, including identifying key performance indicators (KPIs) aligned with organizational goals
  • Shareexpertise, provide feedback, and contribute to industry knowledge and improvement
  • Offer customer-focused insights and solutions by understanding business, product, and customer needs

Embody our and