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Microsoft Corporation Principal Data Scientist - Customer Experience Engineering in Redmond, Washington

The OneDrive and SharePoint (ODSP) organization is in the business of launching new innovative services powering Microsoft 365, Microsoft Copilot and Microsoft Viva. As a member of the ODSP Customer Experience Engineering (CXE) Team, you will be embedded as an integral component of our product development organization and focus on customer insights at scale. Our goal is to drive customer adoption and satisfaction by distilling customer signals into strategic actions.

This role is ideal for candidates passionate about data-driven decision-making and customers with a commitment to helping Microsoft deliver the best possible experience for its global customer base. You will have the unique opportunity to combine your expertise in enterprise software and data science to shape how Microsoft delivers exceptional value to its customers and partners. Your primary responsibilities as a Principal Data Scientist - Customer Experience Engineering will include analyzing customer data to uncover meaningful trends, providing actionable recommendations, and influencing product strategies. We are looking for individuals who bring a fresh perspective and a distinctive voice to foster innovation and excellence within our team.

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

  • Lead the application of data and analytics to uncover key customer insights that drive meaningful business impact.

  • Champion the translation of customer voice data into actionable insights, aligning cross-functional teams to deliver exceptional customer experiences.

  • Influence product strategy and backlogs through data-driven models.

  • Represent the Voice of the Customer (VoC) to senior leadership, crafting and presenting compelling narratives that emphasize critical customer issues surfaced from data analysis to inspire decisive action.

  • Foster collaboration by guiding partnerships with data engineers, CX PMs, and cross-functional teams to define and implement key metrics that achieve strategic business outcomes.

  • Drive innovation by leveraging AI to streamline processes and create scalable self-service solutions.

  • Model technical leadership by being hands-on in developing solutions using Python, SQL, and other relevant technologies.

Qualifications

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 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.

  • 5+ years of experience in SQL, R, Python, or related tools for large-scale analysis.

  • 5+ years of delivering the business impact by working with stakeholders to turn customer voice into insights.

Preferred Qualifications:

  • 5+ years leveraging the practical uses of statistics (i.e. experimentation, sampling)

  • Professional experience with large-scale computing systems like Hadoop, MapReduce, and/or similar systems.

  • 5+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.

  • 10+ years experience in data analysis.

  • Innovative thinking and portfolio of problem-solving using Big Data.

  • Results driven and adaptable; thrives in ambiguous environment.   

  • Interest in contributing to a diverse and inclusive team; demonstrated ability to have fun.

  • Be self-driven and show the ability to deliver on ambiguous projects with incomplete data.

  • Procifient communications & interpersonal skills. Ability to convince other strong personalities of their ideas and communicate complex analysis & insights to a non-technical audience.

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 February 6, 2025.

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 (https://careers.microsoft.com/v2/global/en/accessibility.html) .

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