Microsoft
Senior Data Scientist
Microsoft, Boston, Massachusetts, us, 02298
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. As a part of ISE, at the AI Acceleration Studio we work closely with executives and cross-functional teams as we bring design, data science, and engineering to jointly develop cloud-based solutions that have high impact and can accelerate the organization. We pride ourselves in making contributions to open source and making our platforms easier to use.We are hiring a Senior
Data Scientist
with deep expertise in machine learning and AI and experience in developing production quality solutions which deliver a huge business impact. As part of our team, you will be working with engineers, designers, and data scientists to apply your skills, perspectives, and creativity to trailblaze new ground and build first-of-a-kind AI solutions. 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!ResponsibilitiesBusiness Understanding and Impact
Leads or supports data-science projects or teams to align with business needs and deliver value.Brings new value to the business by leveraging your industry experience in terms of where resources and business needs should be allocated.Leverages extensive experience to drive best practices for discovering, implementing, and maintaining transformative data-science solutions for customers.Data Preparation and Understanding
Contributes and when necessary, leads data acquisition and understanding efforts for engineering projects using various tools and techniques.Modeling and Statistical Analysis
Develops and applies ML frameworks and best practices for scalable and ethical solutions.Has deep mathematical understanding of statistics and machine learning.Incorporates best practices for ML modeling with consideration for artificial intelligence (AI) ethics.Evaluation
Review, supports and provides best practices for data analysis and modeling techniques.Ensures selected modeling techniques are appropriate and align with desired project outcomes.Decide on the next steps (e.g., deployment, further iterations, new projects).Industry and Research Knowledge/Opportunity Identification
Uses business knowledge and technical expertise to provide feedback to the engineering team to identify potential future business opportunities.Develops a better understanding of work being done on team, and the work of other teams to propose potential collaboration efforts.Applies expertise to mitigate technical customer escalations.Coding and Debugging
Writes and debugs code for complex projects and leads solution development.Business Management
Collaborates with end customer and Microsoft internal cross-functional stakeholders to understand business needs.Formulates a roadmap of project activity that leads to measurable improvement in business performance metrics over time.Influences stakeholders to make solution improvements that yield business value by effectively making compelling cases through storytelling, visualizations, and other influencing tools.Customer/Partner Orientation
Provides customer-oriented insights and solutions by understanding the business, product, data, and customer perspective.Develops new techniques/methodologies for building solutions for a specific business need based on available data.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 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.Hands-on experience and demonstrated domain knowledge with Generative AI (GenAI) technologies.Additional Or 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+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.Experience working in Cloud technologies such as Azure.Experience working as part of geographically dispersed, diverse, and virtual teams.
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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. As a part of ISE, at the AI Acceleration Studio we work closely with executives and cross-functional teams as we bring design, data science, and engineering to jointly develop cloud-based solutions that have high impact and can accelerate the organization. We pride ourselves in making contributions to open source and making our platforms easier to use.We are hiring a Senior
Data Scientist
with deep expertise in machine learning and AI and experience in developing production quality solutions which deliver a huge business impact. As part of our team, you will be working with engineers, designers, and data scientists to apply your skills, perspectives, and creativity to trailblaze new ground and build first-of-a-kind AI solutions. 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!ResponsibilitiesBusiness Understanding and Impact
Leads or supports data-science projects or teams to align with business needs and deliver value.Brings new value to the business by leveraging your industry experience in terms of where resources and business needs should be allocated.Leverages extensive experience to drive best practices for discovering, implementing, and maintaining transformative data-science solutions for customers.Data Preparation and Understanding
Contributes and when necessary, leads data acquisition and understanding efforts for engineering projects using various tools and techniques.Modeling and Statistical Analysis
Develops and applies ML frameworks and best practices for scalable and ethical solutions.Has deep mathematical understanding of statistics and machine learning.Incorporates best practices for ML modeling with consideration for artificial intelligence (AI) ethics.Evaluation
Review, supports and provides best practices for data analysis and modeling techniques.Ensures selected modeling techniques are appropriate and align with desired project outcomes.Decide on the next steps (e.g., deployment, further iterations, new projects).Industry and Research Knowledge/Opportunity Identification
Uses business knowledge and technical expertise to provide feedback to the engineering team to identify potential future business opportunities.Develops a better understanding of work being done on team, and the work of other teams to propose potential collaboration efforts.Applies expertise to mitigate technical customer escalations.Coding and Debugging
Writes and debugs code for complex projects and leads solution development.Business Management
Collaborates with end customer and Microsoft internal cross-functional stakeholders to understand business needs.Formulates a roadmap of project activity that leads to measurable improvement in business performance metrics over time.Influences stakeholders to make solution improvements that yield business value by effectively making compelling cases through storytelling, visualizations, and other influencing tools.Customer/Partner Orientation
Provides customer-oriented insights and solutions by understanding the business, product, data, and customer perspective.Develops new techniques/methodologies for building solutions for a specific business need based on available data.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 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.Hands-on experience and demonstrated domain knowledge with Generative AI (GenAI) technologies.Additional Or 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+ years customer-facing, project-delivery experience, professional services, and/or consulting experience.Experience working in Cloud technologies such as Azure.Experience working as part of geographically dispersed, diverse, and virtual teams.
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