Sales Compensation Insights Lead

Job description

**Overview** Applies in-depth knowledge of the business, the evolving data landscape, tools, and technologies, and the lineage of those data across multiple areas. Applies a customer- and/or stakeholder-oriented focus by understanding their needs, perspectives, and how they leverage data insights/tools. Applies expertise in data sources, formats, and quality to identify and leverage data across multiple sources, understands data requirements, and evaluates the sufficiency of data for addressing relevant and impactful business questions. Applies expertise in data, business, and customer needs to evaluate and determine ideal analytical and statistical techniques to address business and/or research questions. Shares insights and analytical expertise to tell stories of analyses through one or more means. Builds, supports, and/or consults others on the execution of formal experiments or prototypes/proofs of concepts. Identifies and promotes methods that create efficiency in core work related to analytics and reporting that are reusable, readily discoverable by decision makers, self-service, and directed to meaningful interpretation of data and driving business decisions. Leverages working relationships within and across teams to ensure alignment and quality execution of data sourcing, methods, model development and application, and the appropriate use of analytical tools and processes. **Responsibilities** **Sales Design and Incentives specific:** - Support design and analysis of incentive compensation plans, aligning them with Microsoft's go-to-market strategies and business objectives. - Conduct advanced modeling, scenario analysis, and performance reviews to evaluate plan effectiveness and provide actionable insights. - Build and maintain robust data pipelines and dashboards to support compensation analytics and reporting needs. - Collaborate with cross-functional teams (e.g., Finance, HR, Sales, Engineering) to ensure compensation strategies are fair, compliant, and optimized for business impact. - Act as a trusted advisor to stakeholders, providing consultation on compensation design, governance, and risk mitigation. - Drive continuous improvement by contributing to global tool development, user acceptance testing (UAT), and process innovation. - Ensure adherence to governance standards and compliance with internal policies and external regulations. Business and Data Landscape Applies in-depth knowledge of the business, the evolving data landscape, tools, and technologies, and the lineage of those data across multiple areas. Links business topics to relevant data sources and external trends, anticipates data and business requirements, and probes for further insights into relevant business- or data-related topics to support data sourcing and integration decisions. Proactively anticipates business questions, develops data frames and analytical solutions, builds connections across business areas, and identifies and acts on opportunities to develop existing, enhanced, or automated data infrastructure, analyses, and solutions that enable the evaluation of business questions. May coach others to help them broaden their knowledge of the business and relevant data sources. Remains up-to-date on latest tools, technologies, best practices in data analytics, and changing regulations. Customer/Stakeholder Orientation Applies a customer- and/or stakeholder-oriented focus by understanding their needs, perspectives, and how they leverage data insights/tools. Validates and advises customer and/or stakeholder requirements, focusing on broader customer organization/context and enables customer adoption by delivering accessible solutions and supporting relationships. Works with customers and/or stakeholders to overcome obstacles, develop tailored and practical solutions, and ensure proper execution. Builds trust with customers and/or stakeholders by leveraging the knowledge of Microsoft products and solutions, interpreting data within relevant contexts, and articulating key details to drive realistic customer expectations and an understanding of the limitations of their data. Data Analysis Applies expertise in data, business, and customer needs to evaluate and determine ideal analytical and statistical techniques to address business and/or research questions. Guides and establishes partnerships with others to execute complex analyses, resolve analytical challenges, interpret results across relevant contexts, and provide actionable recommendations. Critically evaluates the choice of tools, techniques, and assumptions to highlight potential gaps and ensure they are utilized appropriately within context, that outcomes align with business and/or research needs, and provides feedback on features and functions of analytical tools and/or models. Anticipates the risks of data leakage, analytical tradeoffs, methodological limitations, etc., and can guide teammates on solutions. Data Model Evaluation Understands relationship between analytical model(s) and business objectives. Establishes clear linkage between generated data models and desired business objectives to assesses the degree to which data models meet business objectives and highlights gaps or areas that have been missed. Ensures alignment on definitions and standards across stakeholders and defines, designs, and promotes the use of appropriate feedback and evaluation methods. Coaches and mentors less experienced analysts as needed. Presents results and findings to senior stakeholders. Data Privacy and Governance Maintains expertise in data privacy and security requirements, responsible a