Jobs

Principal Data Scientist


Job details
  • Microsoft
  • London
  • 5 days ago

Do you enjoy solving problems, looking at problems through a different lens, and working closely with customers to innovate new solutions to complex problems? Do you jump with excitement at the opportunity to identify trends and provide unique business solutions? Do you want to join a team where learning about a new technology or solution is part of our work every day?

TheIndustry Solutions Engineering(ISE) team is a global engineering organization that works directly with customers looking to leverage the latest technologies to address their toughest challenges. We work closely with our customers engineers to jointly develop code for cloud-based solutions that can accelerate their organization. We work in collaboration with Microsoft product teams, partners, and open-source communities to empower our customers to do more with the cloud. We pride ourselves on making contributions to open source and making our platforms easier to use.

We develop solutions side-by-side with our customers through collaborative innovation to solve their challenges. This work involves the development of broadly applicable, high-impact solution patterns and open-source software assets that contribute to the Microsoft platform. In this role, you will be working with engineers from your team and our customers teams to apply your skills, perspectives, and creativity to grow as engineers and help solve our customers toughest challenges.

We are hiring aPrincipalData Scientistwith deep experience in data management and expertise in developing statistical techniques to analyze data and find patterns. As part of our team, you will be working side-by-side with high-impact engineers and strategic customers to solve complex problems. You will communicate trends and innovative solutions to stakeholders. You will work cross-functionally with several teams including crews, product teams, and program management to deploy business solutions.

Our team prides itself on embracing a growth mindset, inspiring excellence, and encouraging everyone to share their unique viewpoints and be their authentic selves. Join us and help create life-changing innovations that impact billions around the world!

Microsofts 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:

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.

Qualifications:

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 Masters 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 Bachelors 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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