Senior Data Scientist

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At Microsoft for Startups (MfS), we believe in the power of startups to drive innovation and solve the world’s toughest problems. Our team’s mission is to help these companies build, scale, and thrive—by providing them with cutting-edge tools, deep technical expertise, and the insights they need to succeed. As part of our data science team, you’ll be at the heart of this effort, helping to shape intelligent products and programs that fuel the next generation of entrepreneurial success.

As a Senior Data Scientist, you’ll lead high-impact research, build predictive models, and develop metrics that guide strategy across our startup ecosystem. You’ll identify opportunities, design and scope new data projects, and apply advanced machine learning and statistical techniques to real-world challenges. This opportunity will allow you to accelerate your career growth as a technical leader, deepen your expertise in applied AI and cloud technologies, and expand your influence through highly visible, strategic work across Microsoft’s startup programs. We offer flexible work options, and this role can be performed partially or fully from home.

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 1+ 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 3+ 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 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
• 1+ year(s) demonstrated expertise in statistical modeling, experimental design, and causal inference (e.g., A/B testing, natural experiments, observational studies), with a proven track record of applying rigorous statistical methods to generate insights and drive decision-making.
• 2+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.
• 3+ years of experience designing and communicating data visualizations using tools such as Microsoft Power BI, matplotlib, or Plotly, translating complex statistical findings into clear, actionable insights for both technical and non-technical stakeholders.
• 5+ years of experience in data science or machine learning, including building and deploying predictive models using Python, SQL, and common machine learning libraries with a focus on statistical rigor and reproducibility.

Preferred Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ 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 5+ 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 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR equivalent experience.
• 3+ year(s) proven ability to apply AI/ML techniques—including large language models (LLMs), embeddings, and generative AI—to solve real-world business problems.
• 3+ year(s) experience translating academic research or novel statistical methods into practical applications, including familiarity with peer-reviewed literature and emerging techniques in machine learning and causal inference.
• 3+ year(s) strong leadership skills with a track record of mentoring junior data scientists, driving technical excellence, and applying business metrics (e.g., LTV, CAC, churn, conversion funnels) to guide strategic decisions.

Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $158,400 - $258,000 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 July 16, 2025.

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• You will acquire the data necessary for your project plan and develop usable data sets for modeling. You’ll also update internal best practices for data collection and preparation, and contribute to data integrity conversations with customers.
• 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 modeling techniques, and identify 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 multiple features, and develop 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 apply a customer-oriented focus to understand their needs, and help drive realistic customer expectations.