Data Scientist

Redmond, Washington, United States

Microsoft

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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. The Core Search and AI team is the leading applied machine learning team at Microsoft responsible for delivering the highest-quality search experience to over 500M+ monthly active users around the world in Microsoft’s search engine, Bing and other dependent search engines such as Yahoo, DuckDuckGo, and new startups like Neeva.


We are looking for a Data Scientist who wants to build the next generation of search to revolutionize the way people discover and access information by harnessing the power of advanced language models and search technologies, ensuring a personalized, reliable, and inclusive search experience for all users. We are responsible for the largest machine learning models at Microsoft by volume and take pride in being the first in the world to solve many practical AI at Scale challenges. Our work spans a very large scope of scenarios including delivering high quality search results from a massive document corpus, extractive and abstractive summarization to generate document snippets, machine reading comprehension, and document recommendations.

As a team, we leverage the diverse backgrounds and experiences of passionate engineers, scientists, and program managers to help us realize our goal of making the world smarter and more productive. We believe great products are built by inclusive teams of customer-obsessed individuals who trust each other and work together closely.  We collaborate regularly across the company both to find the technology breakthroughs from groups like Microsoft Research to infusing AI into the rest of Microsoft products like Office and Azure.

 

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.

Responsibilities

  • You will help with initial data collection and understand which analysis techniques are appropriate and which tools are necessary for data exploration. You’ll also develop a foundational understanding of methodology and standard statistical options so that you can analyze and organize data as required.
  • You will understand modeling techniques used within the team, then run model tools on prepared data sets. You’ll also analyze model performance and incorporate customer feedback into its evaluation.
  • You will understand the current state of the industry, including current trends, so that you can contribute to thought leadership best practices. You’ll also write code for a specific feature or model, and develop an understanding of proper debugging techniques.
  • Partner effectively with program management, engineers, and other areas of the business

Qualifications

Required Qualifications:

  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
    • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical tec
    • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical tec
    • OR equivalent experience.
  • Experience in Python.

Preferred Qualifications:

  • Understanding of traditional search engine metrics like precision, recall, Mean Reciprocal Rank (MRR), and Normalized Discounted Cumulative Gain (NDCG).
  • Hands-on experience in designing and implementing search engine metrics, preferably with projects that involve LLMs.

Data Science IC3 - The typical base pay range for this role across the U.S. is USD $98,300 - $193,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $127,200 - $208,800 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay

 

Microsoft will accept applications for the role until January 1, 2025.

 

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.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. 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.

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Category: Data Science Jobs

Tags: Azure Computer Science Econometrics Economics LLMs Machine Learning Mathematics ML models Python Research Statistics Unstructured data

Perks/benefits: Career development Medical leave Startup environment

Region: North America
Country: United States

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