Sales Compensation Insights Lead
Sales & Business Development
Hyderabad, Telangana, India
Posted on Jul 21, 2026
Overview
Responsibilities
Business and Data Landscape
Qualifications
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 and ethical data handling and AI 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 activities and results are in alignment with principles and controls. Enforces team standards related to bias, privacy, security, and ethics related to data usage and handling as needed. Knows where to seek expertise on data privacy and security rules and regulations and shares personal knowledge of them with peers as needed to exemplify and enforce standards related to bias, privacy, security, and ethics. Identifies and addresses impact of updated guidance on work activities and results.
Experimentation and Innovation
Builds, supports, and/or consults others on the execution of formal experiments or 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 and/or emerging data sources, as well as decisions related to data use, personalization, and to ensure inferences are appropriate to the data and design when interpreting results. Assesses and takes calculated risks, and applies previous learnings to influence mitigation plans. Synthesizes and connects results across experiments, identifies relevant connections to other work, and makes data-driven recommendations for next steps with clear links to strategic business goals. Determines and recommends optimal and innovative methods, tools, and technologies for operationalizing, sharing, and scaling experimental insights and/or expedite the process.
Expertise in Data
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. Determines and leverages optimal methods and tools for integrating data and proactively works to identify and address data integrity, quality, and/or access issues. Recommends opportunities to build new data pipelines or integrations to better meet requirements, and initiates collaborative action to source additional data. Develops and/or recommends initial/prototype data models and/or tools for others' consumption, leverages relevant data and frameworks from other teams, and escalates complex issues with data or data models to appropriate Engineering or Data-Science teams.
Improvement and Efficiency
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. Recommends and socializes optimal methods for operationalizing, sharing, and scaling insights, shares expertise and a practical rationale for when ad-hoc analyses should become part of regular reporting features. Shares critical domain expertise to create clarity, ensure readiness to appropriately consume and leverage data and/or insights, and evaluate the viability of automated methods for use in data collection, reporting, and/or analysis. Participates in the peer review process and auditing of others' work to ensure quality and relevance of analyses and validate insights.
Orchestration and Collaboration
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. Works with internal stakeholders to identify and promote the adoption of recommended data sources and analysis practices to address business priorities and deliver key insights and results. Seeks opportunities to develop and leverage expertise to identify areas for innovation to address use cases and/or evolving business needs. Proactively engages stakeholders to identify and act on opportunities to leverage data, resources, and solutions that were instrumental to success in similar contexts and consults across teams (e.g., vendors) on decisions related to data sourcing, analyses, and the interpretation of analytical results.
Reporting and Sharing Results
Shares insights and analytical expertise to tell stories of analyses through one or more means, including dashboards, reports, data visualizations, interactive self-service platforms, slides, internal forums, ad-hoc inquiries, and talking points that highlight relevant insights. Synthesizes and simplifies details across analyses and reporting platforms to highlight the most relevant findings that can help inform business decisions and identifies opportunities to improve the efficiency of insights reporting techniques. Guides others and establishes partnerships with stakeholders to ensure results are accessible, and can provide information accurately, clearly, and with sufficient relevance to influence decision making for intended audience(s).
Qualifications
Applying Data Management PrinciplesEnsures data used in solutions is accurate, available, secure and complete. Engages in ongoing improvements to optimize operational efficiency.
Artificial Intelligence (AI) Ethics-Knowledge of issues around fairness, transparency, accountability, and ethics in relation to the use of artificial intelligence (AI).
Data Cleaning-The ability to detect and correct corrupt or inaccurate records from a record set, table, or database and refers to identifying incomplete, incorrect, inaccurate, or irrelevant parts of the data and then replacing, modifying, or deleting as needed to maintain the integrity of the data.
Data Integration-Knowledge of technical and business processes used to combine data from disparate sources into meaningful and valuable information to deliver a complete data integration solution.
Data Integrity-The ability to maintain and assure the accuracy and consistency of data over its entire lifecycle in design, implementation, and usage of systems. This includes knowledge of data governance practices to ensure data quality and defined risk management surrounding the handling of data.
Data Mining-The ability to examine large databases to discover patterns and generate new information. This includes the use of machine learning, statistics, and database systems and aims toward extracting information from a data set and transforming the information into a comprehensive structure for further use.
Data Modeling-Knowledge of data modeling procedures and the ability to identify and clearly define the business data entities (for example, persons, places, things, concepts, events), attributes, and relationships between them. This includes the ability to read, understand, and develop test data models.
Communicating and Influencing Collaboratively-Articulates ideas clearly and engages with stakeholders convincingly. Adapts their communication style to different audiences, ensuring messages are both understood and persuasive.
Conflict Resolution-The ability to manage conflict, disharmony, and strife among people and situations, while recognizing and addressing sensitivities.
CoordinationAbility- to organize the different elements of a complex activity so as to enable them to work together effectively.
Influence Others-The ability to garner support for initiatives by gaining the respect of others and inspiring trust and confidence.
Negotiation-The ability to achieve mutually satisfying agreements in negotiations with others by listening to their objectives, acting as the company's representative to effectively communicate the company's objective, and seeking common ground and collaborative solutions.
Oral CommunicationThe ability to make a verbal message understood and to receive/understand messages during in-person or remote (e.g., telephone) interactions.
Trusted Advisor-The ability to build trusted advisor status and deep relationships across stakeholders (e.g., technical decision makers, business decision makers) through an understanding of customer needs and technologies.
Ensuring Project QualityManages projects and upholds high-quality deliverables, while adhering to compliance and quality assurance protocols. Uses systematic approaches to mitigate risks and optimize project results.
Compliance Oversight-The ability to comply with the rules, regulations, codes, sanctions and other statutory requirements, guidelines and instructions as defined by governing bodies and organizations that regulate and/or set standards or telecommunications and data security/privacy.
Data Evangelism-The ability to inspire others to recognize and understand the importance of data to business goals and engage others to constructively consider how data can be leveraged to improve business, people, and practices.
Documentation-The ability to prepare and deliver documentation in a manner that is consistent with the requirements of the job. It can include work procedures such as logs and forms, as well as technical program system specifications requirements, general reports, legal manuals, and other forms of documentation.
Project Management-Knowledge of and the ability to carry out the process of planning, organizing, and managing tasks and resources to accomplish a well-defined objective. This includes the ability to manage and provide project deliverables, optimize the contribution of the people involved, and assess the impact of project decisions on quality, productivity, schedules, cost, performance, etc.
Quality Assurance-Knowledge of and the ability to follow systematic and continuing processes of checking to see whether a product, service, or process is meeting specified requirements. This includes knowledge of quality measurements and defined standards.
Quality Reviews-Knowledge of quality review and acceptance processes which refer to the extent to which the service fulfills the requirements and expectations of the customer.
Evaluating and Conveying Complex InformationEvaluates and conveys complex information, engages in creative problem-solving, and supports strategic decisions. Applies statistical and financial analysis and attention to detail to guide business choices and optimize outcomes.
Analytical Skills-The ability to review quantitative or conceptual problems and situations to draw appropriate and valid conclusions from data presented. This includes analyzing data to determine the most significant elements, identify common elements and themes in situations and actions, and recognize cause and effect relationships.
Cost Benefit-The ability to apply a systematic approach to estimating the strengths and weaknesses of alternatives (for example in transactions, activities, functional business requirements or projects investments) to determine options that provide the best approach to achieve benefits while preserving savings.
Creativity-The ability to apply ingenuity, inventiveness, and imagination to the inclusive design and construction of a product, service, program, or initiative.
Data Storytelling-The ability to communicate value, interpret data, and provide relevant insights within and outside the company by walking stakeholders through details, decisions, and methods.
Data Visualization-The ability to produce graphic representations of data, including the knowledge of how to communicate relationships among the represented data to various audiences.
Detail Oriented-The ability to attend to and verify the accuracy and completeness of detailed information in documents, on the computer, and/or in other work products. This includes being able to code, file, compile, transcribe, classify, and/or track details from a variety of different sources/problems/issues.
Leveraging Advanced Data Analytics and Automation ExpertiseDesigns and optimizes algorithms, implements machine learning techniques, and uses automation to elevate data utility for strategic decision-making. Manage large-scale data insights with a focus on accuracy and consistency throughout the application's lifecycle.Algorithm Design and Implementation-The ability to design, analyze, implement, optimize, profile and experimentally evaluate computer algorithms. Includes knowledge of practical applications of algorithms in software engineering.
Automation Knowledge of automation technologies, methods, and processes used for quality and cost improvements.
Big Data Knowledge of and ability to use big data, which includes ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. This includes data that is characterized by such a high volume, velocity, and variety to require specific technology and analytical methods for its transformation to value.
Code Review-The ability to apply knowledge about program coding to perform peer reviews of computer source code with the intent to find and fix mistakes, find security loopholes, and correct inefficiencies overlooked in the initial development phase, improving overall code quality.
Machine Learning Knowledge and implementation of an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
Systematic Problem Solving Addresses challenges systemically with a clear orientation towards achieving desired outcomes, even in dynamic and complex environments.
Decision Making-The ability to make decisions in a fast-paced, rapidly changing environment. This includes the ability to define, diagnose, and determine an appropriate resolution, recommendation, or decision while considering alternatives and factors (e.g., resources, costs, tradeoffs).
Dependency Management-The ability to identify and describe the dependencies in relationships within and across systems.
Problem Solving-The ability to identify problems and review related information to develop and evaluate options and implement solutions.
Research-The ability to systematically investigate and study materials and sources in order to establish facts and reach new conclusions.
Results Orientation-The ability to focus on outcome rather than process used to produce a product or deliver a service.
Troubleshooting-The ability to identify and correct problems with products, processes, equipment, software, or other components, as well as their monitoring and regulating.
Required/minimum qualifications
Master's Degree in 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 Bachelor's Degree in Statistics, Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 4+ years experience in data analysis and reporting, data science, business intelligence, or business and financial analysis OR equivalent experience.
Additional or preferred qualifications
Master's Degree in Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 6+ years experience in data analysis and reporting, data science, business intelligence, or business and financial analysis OR Bachelor's Degree in Statistics, Mathematics, Analytics, Data Science, Engineering, Computer Science, Business, Economics or related field AND 8+ years experience in data analysis and reporting, data science, business intelligence, or business and financial analysis OR equivalent experience.
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
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.