Microsoft Principal Data Science Manager 

United Kingdom, England, London 

560958294

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Required/Minimum Qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND some 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 several 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 several years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience.
• People-management experience .

Additional or Preferred Qualifications

• · Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience.
• Demonstrated industry knowledge in one or more of the following sectors: Automotive, Mobility and Transportation [AMT] / Manufacturing and Supply Chain [MSC] / Energy and Sustainability [ENS] and Media and Communications [MNC]

We invest in your health, wellness, and financial future by offering a competitive package including a wide range of benefits built around your personal needs and those close to you.

People Management

• Managers deliver success through empowerment and accountability by modeling, coaching, and caring.
• Model - Live our culture; Embody our values; Practice our leadership principles.
• Coach - Define team objectives and outcomes; Enable success across boundaries; Help the team adapt and learn.
• Care - Attract and retain great people; Know each individual’s capabilities and aspirations; Invest in the growth of others.

Business Understanding

• Leads data-science projects or teams to align with business needs and deliver value.
• Defines and communicates the technical direction and strategy for the team and the project. This involves understanding the project goals, industry trends, and technical delivery context, guiding decision-making, ensuring a focused approach, and alignment with business objectives.
• Provide technical guidance, and suggest best practice, and drive team agreements related to best practices. Offers support to team members as and when required.
• Ensures the quality of the project deliverables is of the required standard. This involves creating clarity on expected standards, and overseeing the implementation to ensure they are adhered to

Data Preparation and Understanding

• Performs, and oversees, extensive exploratory data analysis on large and complex datasets to identify patterns, trends, and relationships, and ultimately generate high quality data and relevant hypotheses. This process involves applying statistical techniques such as hypothesis testing and regression analysis, as well as performing data cleaning, preprocessing, and addressing missing data, outliers, and anomalies to ensure high data quality and reliability.
• Collaborate with stakeholders to understand the specific objectives and goals of project, and aid in designing a formal way of evaluating the systems’ performance against these. This may involve identifying key performance indicators (KPIs) and metrics that align with the organization’s objectives and identifying associations between these and the classical performance indications for models used in the system.

Industry and Research Knowledge/Opportunity Identification

• Provides feedback, drives improvement, and shares knowledge as an Industry data science expert.

Coding and Debugging

• Writes, reviews, and debugs code for complex projects and leads solution development.

Business Management

• Leads data-science partnerships and IP improvement.

Customer/Partner Orientation

• Provides customer-oriented insights and solutions by understanding the business, product, data, and customer perspective.

Responsible AI

• Adheres to Microsoft’s AI Customer Commitment

Culture and values

• Embody Microsoft’s culture and value as the foundation of how we operate