• Advise clients on end-to-end solutions across data strategy, data management, and data quality. • Support business development, methodology development, team leadership, and delivery execution for data governance assessments and implementations. • Design and develop data governance technology solutions across data quality, data dictionaries, business glossaries, data standards, and data policies. • Define organizational design, governance processes, policies, roles, responsibilities, success metrics, and operating models for client data programs. • Build roadmaps covering technology, culture, governance, processes, skills, competencies, data quality, analytics, and data management maturity. • Lead and collaborate with data governance teams to create business cases, resource plans, implementation roadmaps, and enterprise data system assessments. • Assess current-state environments, identify client pain points and requirements, and help define a practical vision and strategy for becoming a data-driven organization. • Advise clients as a trusted partner and provide thought leadership on data governance, data management, cloud transformation, AI readiness, and related best practices. • Manage resources, budgets, project delivery, team development, training, mentoring, and performance assessment.

Role Description 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? Then, come join us! 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. - Work closely with customers’ engineers to jointly develop code for cloud-based solutions. - Collaborate with Microsoft product teams, partners, and open-source communities. - Develop solutions side-by-side with customers through collaborative innovation. - Drive high-impact engineering projects using AI and other cloud-based solutions. - Be part of a cross-functional team of software engineers, data scientists, technical program managers, and designers. As part of our team, you will thrive in working with a variety of technologies, not just Microsoft technology. You will solve exciting business problems, contribute to open source, and collaborate with Microsoft product teams. 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. Responsibilities - Oversee data acquisition and ensure data is properly formatted and described. - Coach engineers in data cleaning and analysis best practices. - Identify gaps in current data sets and drive ethics and privacy discussions around data collection and preparation. - Evaluate team’s models and recommend improvements as necessary. - Drive best practices for models and develop operational models that run at scale. - Conduct thorough reviews of data analysis and modeling techniques. - Research and maintain a deep knowledge of the industry, including trends and technologies. - Write extensible code that spans multiple features. - Define business, customer, and solution strategy goals. - Commit to a customer-oriented focus by acknowledging their needs. Qualifications - Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience. - OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience. - OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience. - OR equivalent experience. Requirements - Microsoft Cloud Background Check: Required to pass upon hire/transfer and every two years thereafter. - Citizenship Verification: Requires verification of U.S. citizenship due to legal restrictions. Preferred Qualifications - The ability to obtain and maintain a United States Security Clearance. - Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience. - OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience. - OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience. - OR equivalent experience. Benefits - Base pay range for this role across the U.S. is USD $142,800 - $274,800 per year. - Different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area is USD $188,000 - $304,200 per year. - Certain roles may be eligible for benefits and other compensation. Company Description Microsoft is an equal opportunity employer. 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 with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

• Identify, evaluate, and advance data center opportunities across the U.S. and the Americas markets. • Support the development of the metro strategy by assessing power availability, scalability, costs, permitting, tax incentives, and regional risk. • Coordinate early technical and commercial feasibility reviews with internal stakeholders. • Lead site-level due diligence including power and utility capacity, substation access, utility timelines, fiber availability, zoning, permitting, environmental considerations, and constructability. • Gather, review, and validate inputs from landlords, utilities, brokers, consultants, and municipalities. • Ensure diligence findings are clearly documented and communicated to leadership. • Support lease negotiations and commercial structuring in partnership with Real Estate and Legal. • Track deal progression, milestones, and deliverables from LOI through execution. • Assist with preparing deal review materials, executive summaries, and approval packages. • Maintain accurate site records, documentation, and status updates in Salesforce and internal tracking systems. • Monitor deal health, proactively flag risks or delays, and ensure data integrity across the Americas pipeline. • Coordinate closely with Transaction Analysts, Program Managers, and Site Diligence teams. • Serve as the primary site-level point of coordination across Engineering, Capacity Planning, Networking, Finance, Legal, and Operations. • Support clean handoff from site selection into delivery, buildout, and operations phases. • Ensure alignment between technical requirements, commercial commitments, and delivery timelines. • Manage relationships with brokers, landlords, utilities, consultants, and development partners across U.S. and Americas markets. • Evaluate inbound site opportunities and ensure consistent screening.

• Analyze large and complex volumes of data using Python, R and Big Data platforms (Spark, Databricks), applying advanced Machine Learning, NLP and Generative AI techniques. • Develop interactive dashboards and reports to support strategic decision-making, using tools such as Power BI or similar. • Create, validate and deploy predictive models and advanced ML algorithms, including Deep Learning and Generative AI applications, to address challenges such as demand forecasting, anomaly detection, process automation, and customer experience personalization. • Integrate models into production environments using MLOps frameworks, ensuring scalability, reliability and efficiency. • Work closely with Engineering, Product, Conversational UX and Data teams, translating business needs into analytical, AI-driven solutions. • Apply Conversational AI techniques, semantic analysis and NLP to extract insights from unstructured and textual data. • Use data augmentation, including LLM-based approaches, to enrich training data and improve model performance.