Principal Data Scientist

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?Then, come join us! The Industry 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.

In this role you would work closely with financial services customers in the capital markets sector 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 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.

We are hiring a Principal Data Scientist to help drive high-impact engineering projects with our financial customers within Capital Markets and their partners, transforming their missions using AI and other cloud-based solutions and services. Data scientists have data management and expertise in developing statistical techniques to analyze data and find patterns. You will be part of a cross-functional team of software engineers, data scientists, technical program managers, and designers who work side-by-side with high-impact and strategic financial customers and their engineers to build innovative solutions.

As part of our team, you will thrive in working with a variety of technologies, not just Microsoft technology. You will solve exciting business problems, contribute to open source, and collaborate with Microsoft product teams.

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.

In alignment with our Microsoft values, we are committed to cultivating an inclusive work environment for all employees to positivelyimpactour culture every day.

Responsibilities

• You will oversee data acquisition and ensure data is properly formatted and described. You'll also coach engineers in data cleaning and analysis best practices, identify gaps in current data sets, and drive ethics and privacy discussions around data collection and preparation.

• You will evaluate your team's models and recommend improvements as necessary, drive best practices for models, and develop operational models that run at scale. You'll also conduct thorough reviews of data analysis and modelingtechniques, andidentify and invent new evaluation methods.

• You will research and maintain a deep knowledge of the industry, including trends and technologies, so that you can identify strategy opportunities and contribute to thought leadership best practices. You'll also write extensible code that spans multiplefeatures, anddevelop expertise in proper debugging techniques.

• You will define business, customer, and solution strategy goals, and partner with other teams to identify and explore new opportunities. You'll also commit to a customer-oriented focus by acknowledging theirneeds, andoffercustomer pragmaticsolutions that align with their data capabilities.

• 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 techniques and reporting results) 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 techniques and reporting results) OR equivalent experience.

Other Requirements

• Experience complying with the strict insider trading rules and informationbarrier requirements of our investment banking customers, including the handling of material nonpublic information.

Additional or preferred qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ 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 10+ 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 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.

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Microsoft is a global technology company headquartered in Redmond, Washington. Our mission is to empower every person and every organization on the planet to achieve more. We develop, license, and support a wide range of software products, services, and devices that help individuals and businesses realize their full potential.

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