Senior Data Scientist

** Overview*
* MCAPS-Core accelerates customer outcomes and business growth. By uniting product, engineering, marketing, sales, customer success, and partners around a common customer mission, we help customers realize value faster and turn innovation into measurable business impact. Through deep technical expertise and differentiated go-to-market execution, we win competitively, capture market share, and scale repeatable growth motions. We differentiate through value creation - delivering world-class, AI-powered customer experiences that accelerate adoption, strengthen loyalty, and create sustainable competitive advantage, driving growth that outpaces the market.

The Office of the Chief Technical Officer (OCTO) organization leads the design of our AI-enabled integrated Customer Success and Support motions across MCAPS-Core and drives the implementation requirements across end-to-end customer experience architectures, improving the quality and experience KPIs across MCAPS-Core. The Data and Applied AI Team is responsible for delivering data-driven decision-making and self-serve analytics to optimize customer experience and support operations across Microsoft's assisted and self-service support surfaces.

We build and manage data platforms and data flows, oversee data and measurement governance, develop Machine Learning (ML) models, manage support-critical data tools, and provide both core and business-specific analytics resources and guidance.

We are looking for a goal-driven Senior Data Scientist with deep experience in developing data driven solutions and expertise in conventional and state of the art Machine Learning (ML) and AI technologies. You will be working side-by-side with high-impact data scientists and strategic customers to solve complex problems. You will work with several teams including engineering crews, product teams, and program management to deploy business solutions.

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*
* + Provides technical leadership for AI-native software engineering by driving adoption of Responsible AI practices, improving AI-enabled development processes, establishing engineering quality measures, mentoring teams on AI-assisted development, and ensuring AI-generated assets meet security, compliance, and quality standards.

+ Owns architecture, engineering excellence, and software quality across complex products by leading system design, code quality strategies, testing frameworks, dependency management, performance optimization, security reviews, and scalable engineering practices while mentoring engineers across teams.

+ Leads secure delivery, operational readiness, and platform reliability by defining deployment and rollback strategies, driving automation and observability, establishing security-by-design principles, managing experimentation frameworks, leading incident response and live-site operations, and ensuring products meet reliability, privacy, compliance, and disaster recovery requirements.

+ Drives cross-team execution and customer-focused innovation by partnering with stakeholders to shape product requirements, align roadmaps, resolve dependencies, incorporate customer and telemetry insights, establish success metrics, and deliver secure, scalable, and highly available solutions that create measurable customer value.

** 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…