Business Intelligence Specialist

Job Description: Seeking a curious, hands-on analytics builder with unmatched quantitative problem-solving skills and the curiosity to bring innovative solutions to reality and transform how our Executive and Equity Compensation team produces reporting, develops insights, and supports high-stakes decisions. This role sits at the intersection of data analytics, business analysis, applied AI, automation, and compensation. You will partner directly with the Director of Executive and Equity Compensation to turn complex and sometimes ambiguous business needs into reliable, scalable analytics products and workflows using AI. You will move from problem definition through prototyping, testing, implementation, and adoption.What You'll Do:Apply a product-centric approach to streamline, re-engineering and automate our recurring monthly, quarterly, and annual reporting, reconciliations, analyses, and decision workflows. This includes evaluating compensation frameworks using quantitative and qualitative data to pinpoint problems and recommending data-backed automated AI solutions.Design, build, and maintain scalable data models, dynamic dashboards, and reporting solutions for use cases such as benchmarking, scenario analysis, grant and equity reporting.Apply company approved AI tools and automation to data preparation, classification, reconciliation, anomaly detection, analysis, narrative generation, and ad hoc question answering, with appropriate human review and controls.Develop AI-enabled workflows, assistants, or agents that are grounded in approved data and documentation and produce reliable, explainable, and useful outputs.Translate ambiguous business questions into clear problem statements, requirements, prototypes, and measurable outcomes.Establish data definitions, quality checks, validation controls, documentation, and monitoring to improve trust, auditability, and repeatability.Create executive-ready visualizations and narratives that turn complex data from Workday, Vizier, and stock administration systems into clear insights, options, and recommendations.Partner across People Analytics, HR Technology, Stock Administration, Payroll, Data and Engineering, Privacy, Security, and Responsible AI.Evaluate tools and build-versus-buy options, create reusable operating practices, and handle highly sensitive information with exceptional discretion and accuracy.What You Bring:3-5 years of relevant experience in either data analytics, business analytics, business systems, data science, finance, consulting, HR analytics, compensation, or a related field. You are a builder and a problem-solver—someone who relies on their technical and analytical prowess to scale ideas.Bachelor's degree in a quantitative, technology, analytics, business systems, or related field - or equivalent practical experience.Practical experience leveraging modern analytics and AI-enabled tools (e.g., ChatGPT Advanced Data Analysis, Claude Code) to accelerate data cleaning, script writing, and reporting; automate workflows; familiarity with prompt design, structured outputs, orchestration, or evaluation is valuable.A proven track record of breaking down complex or ambiguous problems and carrying solutions from concept through launch, adoption, and improvement.Strong proficiency and advanced Excel or Google Sheets strongly preferred; proficiency in SQL Python, R, or another scripting or automation language is a plus but not requiredExperience building data models, working with large and complex datasets, implementing validation and reconciliation controls, and creating dashboards in Power BI, or a comparable platform.Preferred Qualifications:Experience executive compensation, equity compensation, total rewards, people analytics, finance analytics, stock administration, or another adjacent domain.Business System Analyst experience in the domain of Workday or another HRIS, equity administration platformsWhat Success Looks Like:Recurring reports and analyses that are fully automated leveraging AI solutions, documented, and materially less dependent on any manual effort.Data quality, accuracy, auditability, and confidence improve across reporting and decision support.Leaders receive faster, clearer, and more actionable insights, with useful self-service capabilities where appropriate.AI-enabled workflows are grounded, explainable, measurable, secure, and reusable, enabling the team to scale impact without scaling manual work at the same rate.