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Senior Data Scientist

Redmond, WA, US

Pay
Multiple pay statements — pay source
Apply advanced data science techniques, including machine learning, statistical analysis, experimentation, causal inference, segmentation, forecasting, and predictive modeling, to complex customer and business problems. * Translate ambiguous business challenges and user needs into clear analytical approaches and scalable solutions. * Develop solutions around specific users and decision-making scenarios, making insights easier to discover, understand, and act upon. * Explore and apply emerging technologies, including generative AI, large language models, and AI agents, to improve insight generation and analytical experiences. * Rapidly prototype and evaluate new approaches, balancing technical rigor with speed and practical business value. * Build and operationalize analytical and machine learning solutions in partnership with engineering and other technical teams. * Determine when traditional analytics, machine learning, generative AI, or a combination of approaches is best suited to solve a problem. * Evaluate solutions based on both technical quality and real-world effectiveness, including usability, adoption, decision quality, and business impact. * Communicate complex analytical concepts, findings, and recommendations clearly to both technical and non-technical audiences. * Develop reusable analytical methods, frameworks, and capabilities that can scale across users and business scenarios. Qualifications * Experience applying data science, machine learning, applied statistics, or related quantitative techniques to real-world business problems. * Strong proficiency in Python and SQL and experience working with large, complex datasets. * Strong foundation in machine learning, statistical methods, experimentation, model evaluation, and analytical problem solving. * Experience translating ambiguous business questions into structured analytical approaches and actionable recommendations. * Proven ability to partner with users and stakeholders to understand their needs and tailor solutions to specific scenarios. * Experience taking analytical work beyond analysis or model development into solutions, products, or workflows used by others. * Strong communication skills and the ability to influence across technical and non-technical teams. Preferred Qualifications * Experience applying generative AI, LLMs, AI agents, or other emerging AI technologies to analytics, insight generation, or business workflows. * Experience rapidly prototyping, testing, and iterating on new analytical or AI-enabled experiences. * Experience combining traditional data science and machine learning with generative AI or agent-based approaches. * Experience with areas such as personalization, customer analytics, behavioral data, segmentation, recommendation systems, or experimentation. * Experience designing analytical solutions with user experience, adoption, and workflow integration in mind. * Familiarity with responsible AI, model evaluation, governance, and production monitoring. 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 $160,200 - $261,000 per year. Certain roles may be eligible for benefits and other compensation.
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Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: FULL_TIME
From the employer’s posting
Apply at Microsoft

What you’ll work on

Full posting
  • Translate ambiguous business challenges into clear analytical approaches and scalable solutions

  • Build and operationalize analytical and machine learning solutions with engineering teams

  • Prototype and evaluate new approaches, including generative AI and LLM-based methods

  • Evaluate solutions on technical quality, usability, adoption and business impact

  • Communicate analytical findings and recommendations to technical and non-technical audiences

From the employer’s posting
Translate ambiguous business challenges and user needs into clear analytical approaches and scalable solutions.
Build and operationalize analytical and machine learning solutions in partnership with engineering and other technical teams.
Rapidly prototype and evaluate new approaches, balancing technical rigor with speed and practical business value.
Evaluate solutions based on both technical quality and real-world effectiveness, including usability, adoption, decision quality, and business impact.
Communicate complex analytical concepts, findings, and recommendations clearly to both technical and non-technical audiences.

Tools in this posting

  • Python
  • SQL
Source — Tool mentions in context
Apply advanced data science techniques, including machine learning, statistical analysis, experimentation, causal inference, segmentation, forecasting, and predictive modeling, to complex customer and business problems. * Translate ambiguous business challenges and user needs into clear analytical approaches and scalable solutions. * Develop solutions around specific users and decision-making scenarios, making insights easier to discover, understand, and act upon. * Explore and apply emerging technologies, including generative AI, large language models, and AI agents, to improve insight generation and analytical experiences. * Rapidly prototype and evaluate new approaches, balancing technical rigor with speed and practical business value. * Build and operationalize analytical and machine learning solutions in partnership with engineering and other technical teams. * Determine when traditional analytics, machine learning, generative AI, or a combination of approaches is best suited to solve a problem. * Evaluate solutions based on both technical quality and real-world effectiveness, including usability, adoption, decision quality, and business impact. * Communicate complex analytical concepts, findings, and recommendations clearly to both technical and non-technical audiences. * Develop reusable analytical methods, frameworks, and capabilities that can scale across users and business scenarios. Qualifications * Experience applying data science, machine learning, applied statistics, or related quantitative techniques to real-world business problems. * Strong proficiency in Python and SQL and experience working with large, complex datasets. * Strong foundation in machine learning, statistical methods, experimentation, model evaluation, and analytical problem solving. * Experience translating ambiguous business questions into structured analytical approaches and actionable recommendations. * Proven ability to partner with users and stakeholders to understand their needs and tailor solutions to specific scenarios. * Experience taking analytical work beyond analysis or model development into solutions, products, or workflows used by others. * Strong communication skills and the ability to influence across technical and non-technical teams. Preferred Qualifications * Experience applying generative AI, LLMs, AI agents, or other emerging AI technologies to analytics, insight generation, or business workflows. * Experience rapidly prototyping, testing, and iterating on new analytical or AI-enabled experiences. * Experience combining traditional data science and machine learning with generative AI or agent-based approaches. * Experience with areas such as personalization, customer analytics, behavioral data, segmentation, recommendation systems, or experimentation. * Experience designing analytical solutions with user experience, adoption, and workflow integration in mind. * Familiarity with responsible AI, model evaluation, governance, and production monitoring. 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 $160,200 - $261,000 per year. Certain roles may be eligible for benefits and other compensation.

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Actively hiringFirst seen by us 6 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 23, 2026 · 6 days ago
Recorded sightings
41
Last seen by us
Oct 30, 2026

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Job description

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Apply advanced data science techniques, including machine learning, statistical analysis, experimentation, causal inference, segmentation, forecasting, and predictive modeling, to complex customer and business problems. * Translate ambiguous business challenges and user needs into clear analytical approaches and scalable solutions. * Develop solutions around specific users and decision-making scenarios, making insights easier to discover, understand, and act upon. * Explore and apply emerging technologies, including generative AI, large language models, and AI agents, to improve insight generation and analytical experiences. * Rapidly prototype and evaluate new approaches, balancing technical rigor with speed and practical business value. * Build and operationalize analytical and machine learning solutions in partnership with engineering and other technical teams. * Determine when traditional analytics, machine learning, generative AI, or a combination of approaches is best suited to solve a problem. * Evaluate solutions based on both technical quality and real-world effectiveness, including usability, adoption, decision quality, and business impact. * Communicate complex analytical concepts, findings, and recommendations clearly to both technical and non-technical audiences. * Develop reusable analytical methods, frameworks, and capabilities that can scale across users and business scenarios. Qualifications * Experience applying data science, machine learning, applied statistics, or related quantitative techniques to real-world business problems. * Strong proficiency in Python and SQL and experience working with large, complex datasets. * Strong foundation in machine learning, statistical methods, experimentation, model evaluation, and analytical problem solving. * Experience translating ambiguous business questions into structured analytical approaches and actionable recommendations. * Proven ability to partner with users and stakeholders to understand their needs and tailor solutions to specific scenarios. * Experience taking analytical work beyond analysis or model development into solutions, products, or workflows used by others. * Strong communication skills and the ability to influence across technical and non-technical teams. Preferred Qualifications * Experience applying generative AI, LLMs, AI agents, or other emerging AI technologies to analytics, insight generation, or business workflows. * Experience rapidly prototyping, testing, and iterating on new analytical or AI-enabled experiences. * Experience combining traditional data science and machine learning with generative AI or agent-based approaches. * Experience with areas such as personalization, customer analytics, behavioral data, segmentation, recommendation systems, or experimentation. * Experience designing analytical solutions with user experience, adoption, and workflow integration in mind. * Familiarity with responsible AI, model evaluation, governance, and production monitoring. 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 $160,200 - $261,000 per year. Certain roles may be eligible for benefits and other compensation.
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