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Private Company | Business Intelligence Analyst | Redmond, WA | United States | BigDataKB.com | 2023/01/18

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Job Location: Redmond, WA

Job Detail:


  • Understanding the Business : Applies in-depth knowledge of the business to proactively identify and address business concerns. Takes measures to determine scope and impact to develop appropriate solutions, builds and leverages connections between their business and Microsoft’s other business areas, clearly articulates connections between internal business topics and relevant external trends, and includes key stakeholders in scoping process. Seeks out opportunities to coach others to broaden business knowledge.
  • Expertise : Establishes themselves as an expert in data types and sources relevant to business needs, and shares expertise to guide others. Evaluates sufficiency of data for answering business questions between internal and external sources, and works to identify, anticipate, and address gaps and data quality issues with data providers; drives action to source additional data as needed, and leverages relevant frameworks from others teams. Collaborates with Engineering teams to build needed data pipelines or integrations to address business needs and develops and advises other analysts on ideal ways to present and discuss data to influence business stakeholders’ decision making.
  • Data Analysis: Applies expertise in data, business, and customer/client needs to determine optimal analytical tools and techniques, and leads others through the execution of analyses to resolve analytical challenges, interpret results within a business context, and address business questions with actionable insights and recommendations. Identifies gaps in analytical tools, provides feedback on features and/or functions, and recommends changes for Engineering or Data Science teams to improve tools, and/or techniques with the goal of ensuring that outputs align with business needs.
  • Presentation of Results: Develops and guides others’ work on presentations of analyses, including dashboards, reports, data visualizations, self-service platforms, slides, and talking points that synthesize insights into a story that influences senior stakeholders’ decision making and drives business outcomes. Actively supports efforts to improve efficiency of reporting and presentations, and guides others to ensure presented results are accessible, provide information accurately, clearly, and appropriately in a relevant and timely manner to influence decision making for intended audience(s).
  • Evaluation : Determines preferred factors and/or data types to include in the evaluation of business, product, and/or operational decisions that will provide the most relevant assessment of impact. Independently ensures that evaluations account for anticipated risks and applies learnings from previous evaluations. Proactively synthesizes and connects results across evaluation instances and identifies relevant connections to other work to make recommendations that drive achievement of strategic business goals.
  • Orchestration and Collaboration: Establishes and leverages working relationships within and across teams to ensure quality data sources, methodologies, and analytical tools and processes; driving their adoption to address business needs and deliver key insights and results. Proactively seeks to leverage resources and solutions that were instrumental to success in similar contexts, and shares expertise across teams to inform decisions related to analyses, insights reporting, and the interpretation of results.
  • Improvement, Efficiency, Innovation : Drives the implementation of methods that create efficiency in core work related to analytics and reporting that are reusable, readily discoverable, self-service, and directed to meaningful interpretation of data that drive business decisions and impact across teams. Determines and socializes optimal and innovative methods for standardizing, sharing, and scaling insights. Evaluates the viability of implementing automation for patterns of ad hoc analyses or reporting into standard practices, and shares thought leadership in partnership with Engineering or Data Science teams to develop and implement automated methods for use in data collection and analysis that are most relevant to addressing business needs.

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