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?

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. 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 in 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 a Principal Data Scientist with deep experience in data management and experience 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!

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

Business Understanding and Impact

• Leverages subject matter expertise to analyze problems and issues facing projects to uncover, manage, and/or mitigate factors that can influence final outcomes across product lines. Partners with business team to drive strategy and recommend improvements. Raises opportunities to look for new work opportunities and different contexts to use existing work. Establishes, applies, and teaches standards and best practices.
  
  

Data Preparation and Understanding

• Oversees data acquisition efforts and ensures data is properly formatted and accurately described. Utilizes key technologies and tools necessary for data exploration (eg: Python). Uses querying, visualization, and reporting techniques to explore the data, including distribution of key attributes, relationships between attributes, simple aggregations, properties of significant sub-populations, and statistical analyses. Mentors and coaches engineers in data cleaning and analysis best practices. Identifies gaps in current data sets and drives onboarding of new data sets (e.g., bringing on third-party data sets). Drives discussions around ethics and privacy policies related to collecting and preparing data. Integrates industry-wide ethics insights and best practices to influence internal processes and drive decision-making. Builds data platforms from scratch across products. Builds data-science business solutions using existing technologies, products, and solutions, as well as established patterns and practices. Provides guidance on model operationalization of models created by data scientists. Identifies new opportunities from data and processes data in a way that is usable for general purpose. Actively contributes to the body of thought leadership and intellectual property (IP) on best practices for data acquisition and understanding. Leads and resolves data-integrity problems.
  
  

Modeling and Statistical Analysis

• Generalizes machine learning (ML) solutions into repeatable frameworks (e.g., modules, packages, general-purpose software) for others to use. Exemplifies and enforces team standards related to bias, privacy, and ethics. Evaluates the methodology and performance of teammates’ models and, as appropriate, recommends solutions for improvement. Anticipates the risks of data leakage, the bias/variance tradeoff, methodological limitations, etc., and is able to guide teammates on solutions. Drives best practices relative to model validation, implementation, and application. Develops operational models that run at scale. Partners with others to identify and explore opportunities for the application of ML and predictive analysis. Identifies new customer opportunities for driving transformative customer solutions with ML modeling. Incorporates best practices for ML modeling with consideration for artificial intelligence (AI) ethics. Develops deep expertise in specialized areas by staying abreast of current and emerging methodologies an AI and ML.
  
  

Evaluation

• Conducts thorough review of data analysis and techniques used to summarize the process review and highlight areas that have been missed or need reexamining. Utilizes results of the assessment and process review to decide on next steps (e.g., deployment, further iterations, new projects). Identifies new evaluation approaches and metrics and invents new methodologies to evaluate models.
  
  

Industry and Research Knowledge/Opportunity Identification

• Tracks advances in industry and academia, identifies relevant state-of-the-art research, and adapts algorithms and/or techniques to drive innovation and develop new solutions. Researches and maintains deep knowledge of industry trends, technologies, and advances. Leverages knowledge of work being done on team to propose collaboration efforts. Proactively develops strategic responses to specific market strengths, weaknesses, opportunities, threats, and/or trends. Mentors and coaches less experienced engineers in data analysis best practices. Serves as a subject matter expert and role model for less experienced engineers. Identifies strategy opportunities. Actively contributes to the body of thought leadership and intellectual property (IP) best practices by actively participating in external conferences.
  
  

Coding and Debugging

• Independently writes efficient, readable, extensible code/model that spans multiple features/solutions. Contributes to the code/model review process by providing feedback and suggestions for implementation and improvement. Develops expertise in proper modeling, coding, and/or debugging techniques such as locating, isolating, and resolving errors and/or defects. Leads a project team in the gathering, integrating, and interpreting of data/information from multiple sources in order to properly troubleshoot errors. Provides feedback on non-optimized features/solutions back to product group, and explores potential for new features. Leverages expert-level proficiency of big-data software engineering concepts, such as Hadoop Ecosystem, Apache Spark, continuous integration and continuous delivery (CI/CD), Docker, Delta Lake, MLflow, AML, and representational state transfer (REST) application programming interface (API) consumption/development.
  
  

Business Management

• Defines business-strategy goals, customer-strategy goals, and solution-strategy goals. Partners with teams to identify and explore opportunities for the application of machine learning (ML) and other data-science tools. Leverages technical experience to develop partnerships between product teams, Sales teams, Area teams, and Services. Work collaboratively across disciplines. Leads involvement of intellectual property (IP) definition improvement. Coaches and mentors less experienced engineers.
  
  

Customer/Partner Orientation

• Commits to a customer-oriented focus by acknowledging customer needs and perspectives, validating customer perspectives, focusing on broader customer organization/context, and serving as a trusted advisor. Identifies opportunities and adds valuable insight by incorporating an understanding of the business, product/service functionality, data sources, methodologies to reframe problems, and the customer perspective. Interprets results, develops insights, and effectively communicates results to the customer. Leads the discussion with customers and offers pragmatic solutions that are feasible given their data limitations.
  
  

Other

• Embody our culture and values
  
  

Qualifications

Required/Minimum Qualifications

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ year(s) 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

Citizenship & Citizenship Verification: This position requires verification of U.S citizenship due to citizenship-based legal restrictions. Specifically, this position supports United States federal, state, and/or local United States government agency customers and is subject to certain citizenship-based restrictions where required or permitted by applicable law. To meet this legal requirement, citizenship will be verified via a valid passport, or other approved documents, or verified US government clearance.

Citizenship & Citizenship Verification: This role will require access to information that is controlled for export under U.S. export control regulations, potentially under the International Traffic in Arms Regulations or the Export Administration Regulations. As a condition of employment, the successful candidate will be required to provide proof of citizenship, U.S. permanent residency or other protected status under 8 U.S.C.

• 1324b(a)(3) for assessment of eligibility to access the export-controlled information. To meet this legal requirement, citizenship will be verified via a valid passport.
  
  

Cloud Screening

Candidates must be able to successfully complete and pass a Microsoft Cloud background screening. Required Cloud Screenings will be administered on a recurring bi-annual basis.

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.
• Ability to obtain and maintain a United States Security Clearance.
  
  

Data Science IC5 - The typical base pay range for this role across the U.S. is USD $137,600 - $267,000 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 $180,400 - $294,000 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 August 3, 2024.

#ISEngineering

Microsoft is an equal opportunity employer. Consistent with applicable law, all qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.