Job Location: Redmond, WA
The Master Data Management team is responsible for building and maintaining connected and trusted single source of truth for 3rd party commercial organization data (Customers/partners/suppliers) for Microsoft eco-system, as well as integrating the master data with Microsoft core systems from marketing to cash
Responsibilities
Business and Data Landscape
- Develops depth of understanding of the business, its data landscape, and the lineage of those data across multiple areas. Considers relevant data sources and external trends, anticipates data requirements, and probes for insight to understand business- or data-related topics beyond stated concerns. Identifies connections and themes across first and/or third-party data sources and anticipates opportunities to leverage those connections and themes to contribute to the development of data infrastructure and analytical frameworks that enable the evaluation of business questions.
Customer/Stakeholder Orientation
- Leverages understanding of data and the business to examine projects through a customer- and/or stakeholder-oriented focus. Manages customer and/or stakeholder expectations regarding project/product progress and timeline and takes responsibility to enhance customer excellence. Assists and learns from senior team members to interpret results, develop insights, and communicate results to customers and/or stakeholders. Possesses a basic understanding of model accuracy and its dependency on data quality and can articulate these topics in relevant terms in customer or stakeholder discussions.
Expertise in Data
- Identifies and leverages appropriate sources of data to address specific business needs. Evaluates data for applicability to answering relevant and impactful business questions, determines methods for integrating data across sources, and addresses data integrity and/or quality issues independently and/or in partnership with other teams. Contributes to the development and/or recommendation of initial/prototype data models and/or tools for consumption by others and escalates complex issues with those models and/or tools to appropriate Engineering or Data-Science teams.
Data Analysis
- Determines appropriate analytical and inferential techniques to address business questions, executes analyses and interprets results with actionable recommendations, and partners to build on others’ analyses and frameworks. Critically evaluates the choice of tools, techniques, and assumptions to ensure they are appropriate within context and provides feedback on features and functions of analytical tools and/or models.
Reporting and Sharing Results
- Shares and simplifies relevant findings and insights to tell stories of analyses through one or more means including dashboards, reports, data visualizations, self-service platforms, slides, internal forums, ad-hoc inquiries, and/or talking points. Ensures presented results are accessible, provides information accurately and clearly, and appropriately speaks to the needs of the intended audience(s). Recommends and makes improvements to insights reporting as appropriate.
Experimentation and Innovation
- Supports and/or consults with other teams on the build and execution of formal experiments or develops prototypes/proofs of concepts, to evaluate the impact of new or changed features or processes. Partners cross-functionally to advise on experimental design or evaluation frameworks for established data sources, as well as decisions related to data use, personalization, and the interpretation of results. Takes calculated risks and applies learnings, reports results, and identifies relevant data-driven recommendations and/or connections to results of other work.
Improvement and Efficiency
- Recommends efficiency improvements for core work related to analytics and reporting that are reusable, self service, and directed to meaningful interpretation of data and driving business decisions. Makes recommendations for efficient methods for conducting ad-hoc analyses, and whether to make them standard. Shares domain knowledge to create clarity, support readiness to consume and leverage data and/or insights and evaluate the viability of automated methods for use in data collection, reporting, and/or analysis.
Model Evaluation
- Understands linkages between analytical model(s) and business objectives. Assists with testing models on test applications; analyzes model performance; and incorporates implicit and explicit customer feedback into model evaluation. Conducts review of data analysis and modeling techniques to determine factors that may have been overlooked or need to be reexamined. Contributes to the summary of the review process. If model deemed deficient, seeks to determine why.
Orchestration and Collaboration
- Works within and across teams to ensure alignment in data sources, methods, models, analytical tools and processes, and business priorities to deliver key insights and results. Engages stakeholders to identify and act on opportunities to leverage resources, data sources, and solutions that were instrumental to success in similar contexts and consults across teams on decisions related to data sourcing, analyses, and the interpretation of analytical results.
Data Privacy and Governance
- Stays abreast of data privacy requirements, responsible and ethical data handling practices, and models compliance with classification and governance rules and regulations. Ensures data have undergone appropriate Corporate, Executive, and Legal Affairs (CELA) reviews and ensures work products are in alignment with principles and controls and is aware of where to seek further expertise on data privacy rules and regulations when needed to determine the impact of updated guidance on work activities and results.
Qualifications
Basic Qualifications:
-
Bachelor’s Degree in Statistics, Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 2+ years experience in data analysis and reporting, data science, business intelligence, or business and financial analysis
- OR Master’s Degree in Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field
- OR equivalent experience.
Preferred Qualifications:
- Bachelor’s Degree in Statistics, Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 3+ years’ experience in data analysis and reporting, data science, business intelligence, or business and financial analysis
- OR Master’s Degree in Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 1+ year(s) experience in data analysis and reporting, data science, business intelligence, or business and financial analysis
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
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