Microsoft Principal Data Scientist 

United Kingdom, England, London 

755115170

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Required Qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND relevant 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 significant 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 significant years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience.
• Customer-facing, project-delivery experience, professional services, and/or consulting experience.

Preferred Qualifications

• Proficient in Python with experience in Pandas, Scikit-learn, and the Python ML stack; strong coding skills for developing and maintaining machine learning models.
• Proficient in additional programming languages such as C#, Java, and C/C++.
• Skilled in building and maintaining models in various domains, including computer vision, forecasting, recommendation systems, and NLP.
• Experienced with agile development practices and Git version control.
• Familiar with deep learning frameworks like TensorFlow or PyTorch; experience with GenAI/LLMs is a plus.
• Experienced in the operational aspects of machine learning, including deployment, monitoring, and continuous integration of ML models.
• Expertise in domains such as financial services, retail, marketing, healthcare, manufacturing, media, or telecommunications.
• Effective at communicating technical models in business and technical contexts.
• Familiarity with Spark, SQL, Graph stores, or NoSQL stores is helpful.

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Business Understanding and Impact

• Leads data-driven projects with business acumen and data science expertise.

Data Preparation and Understanding

• Manages data collection and preparation for projects.

Modeling and Statistical Analysis

• Applies machine learning solutions and algorithms to achieve objectives, prepare and evaluate data, and communicate findings and risks. Writes scripts in various languages and understands Microsoft AI and ML tools. Designs experiments and operationalizes models at scale. Coaches junior engineers on best practices.

Evaluation

• Understands relationship between selected models and business objectives. Ensures clear linkage between selected models and desired business objectives. Defines and designs feedback and evaluation methods. Coaches and mentors less experienced data & applied scientists. Presents results and findings to senior customer stakeholders.

Industry and Research Knowledge/Opportunity Identification

• Provides feedback, coaching, and support to engineering team and other teams based on business knowledge, technical expertise, and industry trends.

Coding and Debugging

• Demonstrates excellent coding and debugging skills across multiple features/solutions.

Business Management

• Drives business value by collaborating with stakeholders and improving solutions.

Customer/Partner Orientation

• Delivers customer-oriented solutions and builds trust with Microsoft products.