Principal Data Scientist Manager

We are looking for a motivated, self-driven Principal Data Scientist leader to join our mission on power best sport experience on Bing. Essential attributes and competencies include excellence in scientific thinking and execution, ability to drive efficient experiment definition and investigations, solid skill in developing state-of-the-art machine learning algorithms and broad scope in solving NLU related ML problems.

Microsoft’s 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.

Required Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years 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 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techn
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical te
  • OR equivalent experience.
• 3+ years people-management experience.
• 10+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.
• 5+ Years of experience in deep learning (extensive work on NLP is a plus).

Additional or Preferred Qualifications:

• Published work in top-tier conferences & journals.
• Ability to synthesize the research literature, compare/contrast/critique and combine ideas into creating new ML models.
• Experience in building, deploying, and improving large scale Machine Learning models and algorithms in real-world products.
• Research or Industry experience with one or more of following areas Natural Language Processing (NLP), Document Understanding, Information Retrieval, Natural Language Understanding.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

• Build and refine machine learning models to solve NLP tasks and productizing the solutions at scale. Staying abreast with the SOTA advancements and use them to formulate novel solutions.
• Advancing the state of the art of NLP technologies for real world scenarios.
• Developing novel machine learning and data mining algorithms. Contribute ideas and techniques to shape decisions and improve product quality metrics.
• Participate in design, implementation and execution with a team of engineers, applied scientists and product managers.
• Collaborate with Program Managers and stakeholders to create and architect innovative end-to-end solution design. Mentor and provide technical guidance to a diverse high-performance team of Data Scientists
• Create clarity, generate energy and deliver the impact
• Ensuring compliance with Security, Privacy, GDPR etc. and performance criteria. Use data and insights from customer and production to contribute to some technical design and implementation decisions.