Workiva

Compensation

Full Description

Job Description: • Define and own the multi-year Data Science and BI strategy and roadmap, ensuring direct alignment with enterprise priorities and quantifiable business outcomes (e.g., revenue growth, operational efficiency) • Recruit, mentor, and manage a high-performing, multi-disciplinary team of Data Scientists, BI Analysts, and BI Engineers, establishing a culture of innovation, operational excellence, and continuous professional development • Act as the primary analytic partner to business unit leaders (Sales, Product, CS, Marketing, etc.) to define and deliver high-impact, decision-support data products, including predictive models and AI-powered self-service insights • Translate complex, ambiguous business challenges into structured analytical strategies, guiding teams to deliver high-quality, decision-ready solutions • Drive an agile, iterative delivery process and oversee end-to-end predictive model lifecycle management, from ideation and validation through scalable deployment, monitoring, and optimization • Communicate clear, actionable, and data-driven recommendations to all audiences, including senior and executive leadership, shaping strategy through compelling, tailored narratives • Collaborate closely with Data Engineering and Analytics Engineering to design and scale enterprise data assets, features, and metrics that meet evolving analytical needs • Establish and enforce best practices for metrics design, experimentation, and data governance. Champion data ethics, compliance, and responsible AI standards to promote transparency and trust • Partner with leaders across Data Platform, Data Product Management, and Data Governance to develop and execute the overarching Enterprise Data Strategy Requirements: • 8+ years of experience in Data Science, Machine Learning, or related analytical fields, including 3+ years leading high-performing technical teams • Advanced degree (MS/PhD) in a quantitative discipline (e.g., Computer Science, Statistics, Mathematics, Operations Research, or similar) • Demonstrated ability to translate ambiguous business problems into analytical frameworks and deliver measurable business impact • Experience in SaaS or B2B environments, especially where data products directly enable go-to-market, customer success, or product strategy • Hands-on experience deploying and operating ML models in production, including monitoring, optimization, and lifecycle management Benefits: • A discretionary bonus typically paid annually • Restricted Stock Units granted at time of hire • 401(k) match and comprehensive employee benefits package