Microsoft
Overview
Join to apply for the
Senior Data Scientist
role at
Microsoft . If you have an interest in data and are committed to developing systems that enhance informed decision-making at Microsoft, the Insights, Data Engineering & Analytics team offers a platform for professional growth. This role leads advanced analytics initiatives to drive business insights and strategic decisions. You will design and implement scalable data solutions, apply rigorous statistical methods, and develop predictive models that influence product and business outcomes. This role requires strong technical depth, business acumen, and the ability to mentor team members. This team supports Microsoft 365 and the Experiences + Devices group (E+D), with a focus on equipping the organization with actionable insights to guide decisions and improve operational efficiency in an evolving AI landscape. The IDEAS Data Science team (Business Pillar) specializes in transforming complex data into actionable business insights by building robust analytical frameworks and predictive models that drive strategic decisions across the organization. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we strive for growth, innovation, and collaboration guided by respect, integrity, accountability, and inclusion.
Responsibilities
Design and execute controlled experiments to validate hypotheses.
Apply advanced statistical techniques (e.g., regression, Bayesian methods, causal inference) to derive actionable insights.
Communicate limitations and confidence intervals clearly to stakeholders.
Develop predictive and prescriptive models using machine learning and AI techniques.
Ensure models are production-ready, maintainable, and aligned with privacy and compliance standards.
Monitor model performance and iterate based on telemetry and feedback.
Build ad hoc and production-ready data pipelines for large-scale, diverse datasets.
Partner with Data Engineering teams to ensure robust, secure, and scalable data infrastructure.
Implement best practices for data quality, governance, and monitoring.
Translate complex analytical findings into clear business recommendations.
Influence product and strategy decisions through data-driven insights.
Collaborate with cross-functional teams to align analytics with organizational goals.
Coach data scientists on technical skills and best practices.
Drive adoption of efficient processes and tools across teams.
Contribute to defining standards for experimentation and analytics.
Adopt new AI/LLM technologies.
Embody our culture and values.
Qualifications 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.
3+ years of experience with SQL, R, Python to implement statistical models, machine learning, and analysis (Recommenders, Prediction, Classification, Clustering, etc.) in big data environment.
2+ years of experience with written and verbal communication to educate and work with cross functional teams.
1+ year of experience in delivering on ambiguous projects with incomplete or imperfect data.
Other Requirements:
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. This includes Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.
Preferred Qualifications:
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience.
OR Master’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience.
OR Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience OR equivalent experience.
3+ years of experience with SQL, R, Python to implement statistical models, machine learning, and analysis in big data environment.
Experience on large-scale computing systems like COSMOS, Hadoop, MapReduce and/or similar systems.
Experience with programming skills, e.g. Java, C#.
Familiarity with deep learning toolkits, e.g. CNTK, TensorFlow.
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 October 24, 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.
#J-18808-Ljbffr
Join to apply for the
Senior Data Scientist
role at
Microsoft . If you have an interest in data and are committed to developing systems that enhance informed decision-making at Microsoft, the Insights, Data Engineering & Analytics team offers a platform for professional growth. This role leads advanced analytics initiatives to drive business insights and strategic decisions. You will design and implement scalable data solutions, apply rigorous statistical methods, and develop predictive models that influence product and business outcomes. This role requires strong technical depth, business acumen, and the ability to mentor team members. This team supports Microsoft 365 and the Experiences + Devices group (E+D), with a focus on equipping the organization with actionable insights to guide decisions and improve operational efficiency in an evolving AI landscape. The IDEAS Data Science team (Business Pillar) specializes in transforming complex data into actionable business insights by building robust analytical frameworks and predictive models that drive strategic decisions across the organization. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we strive for growth, innovation, and collaboration guided by respect, integrity, accountability, and inclusion.
Responsibilities
Design and execute controlled experiments to validate hypotheses.
Apply advanced statistical techniques (e.g., regression, Bayesian methods, causal inference) to derive actionable insights.
Communicate limitations and confidence intervals clearly to stakeholders.
Develop predictive and prescriptive models using machine learning and AI techniques.
Ensure models are production-ready, maintainable, and aligned with privacy and compliance standards.
Monitor model performance and iterate based on telemetry and feedback.
Build ad hoc and production-ready data pipelines for large-scale, diverse datasets.
Partner with Data Engineering teams to ensure robust, secure, and scalable data infrastructure.
Implement best practices for data quality, governance, and monitoring.
Translate complex analytical findings into clear business recommendations.
Influence product and strategy decisions through data-driven insights.
Collaborate with cross-functional teams to align analytics with organizational goals.
Coach data scientists on technical skills and best practices.
Drive adoption of efficient processes and tools across teams.
Contribute to defining standards for experimentation and analytics.
Adopt new AI/LLM technologies.
Embody our culture and values.
Qualifications 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.
3+ years of experience with SQL, R, Python to implement statistical models, machine learning, and analysis (Recommenders, Prediction, Classification, Clustering, etc.) in big data environment.
2+ years of experience with written and verbal communication to educate and work with cross functional teams.
1+ year of experience in delivering on ambiguous projects with incomplete or imperfect data.
Other Requirements:
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. This includes Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.
Preferred Qualifications:
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience.
OR Master’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience.
OR Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience OR equivalent experience.
3+ years of experience with SQL, R, Python to implement statistical models, machine learning, and analysis in big data environment.
Experience on large-scale computing systems like COSMOS, Hadoop, MapReduce and/or similar systems.
Experience with programming skills, e.g. Java, C#.
Familiarity with deep learning toolkits, e.g. CNTK, TensorFlow.
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 October 24, 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.
#J-18808-Ljbffr