Data Science
Job Description
Description
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With more than 45,000 employees and partners worldwide, the Customer Experience and Success (CE&S) organization is on a mission to empower customers to accelerate business value through differentiated customer experiences that leverage Microsoft’s products and services, ignited by our people and culture. We drive cross-company alignment and execution, ensuring that we consistently exceed customers’ expectations in every interaction, whether in-product, digital, or human-centered. CE&S is responsible for all up services across the company, including consulting, customer success, and support across Microsoft’s portfolio of solutions and products. Join CE&S and help us accelerate AI transformation for our customers and the world.
Within CE&S, the Customer Service & Support (CSS) organization builds trust and confidence for every person and organization through delivering a seamless support experience. In CSS, we are powered by Microsoft’s AI technology to help consumers, businesses, partners, and more, resolve their issues quickly and securely, helping prevent future problems from occurring and achieving more from their Microsoft investment.
We are seeking a Data Scientist with deep expertise in statistical modeling and machine learning to advance our understanding of support case dynamics and operational efficiency. This role will focus on developing AI/ML algorithms to assess case complexity, model labor time within support workflows, and uncover insights that drive measurable improvements in throughput and resource utilization. The ideal candidate will bring a strong foundation in regression analysis, causal inference, and experimentation, contributing to a data science practice that is central to operational excellence and transformation across CSS.
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
Application of AI (AOAI) & Efficiency Measurement:
- Develop and implement causal inference models and statistical frameworks to quantify labor effort within support cases—including active engineer time, idle time, and wait time. Extend these models to evaluate the impact of AI-driven systems (e.g., AOAI agents) on case resolution efficiency, agentic throughput, and cost avoidance. Leverage telemetry, case metadata, and experimental design to isolate AI contributions and optimize support workflows.
Productivity And Throughput Analytics
- Build predictive models and dashboards to analyze throughput, case complexity, and routing efficiency. Apply statistical and machine learning techniques to surface process defects, blind transfers, and excessive case handoffs.
Agentic & Autonomous System Evaluation
- Collaborate with engineering and supportability teams to evaluate autonomous agent performance. Develop capacity models and performance metrics to assess agentic build-out efficiency and ROI.
- 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. Exemplifies and enforces team standards related to bias, privacy, and ethics.
Business Understanding And Impact
- Understands problems facing projects and is able to leverage knowledge of data science to be able to uncover important factors that can influence outcomes on specific products. Describes the primary objectives of the team from a business perspective. Produces a project plan to specify necessary steps required for completion. Assesses current situation for resources, risks, contingencies, requirements, assumptions, and constraints. Coaches less experienced engineers in standards and best practices. Understanding of organizational dynamics, interrelationships among teams, schedule constraints, and resource constraints to effectively influence partners to take action on insights. Understands business strategy briefings and articulates data driver strategies for specific industries or cross-industry functions, such as: Sales/Marketing, Operations, and new Data Monetization Schemes. Engages business stakeholders to capture and shape their thinking on data-driven methods applicable to their value chain. Leads customer conversations to understand, define, and solve business problems.
Coding And Debugging
- Writes efficient, readable, extensible code from scratch that spans multiple features/solutions. Develops technical expertise in proper modeling, coding, and/or debugging techniques such as locating, isolating, and resolving errors and/or defects. Understands the causes of common defects and uses best practices in preventing them from occurring. Collaborates with other teams and leverages best practices from those teams into work of their own team. Mentors and guides less experienced engineers in better understanding coding and debugging best practices. Builds professional-grade documents for knowledge
Company
Microsoft
Location
, YT, Canada
Country
Canada
Salary
100.000
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