Director of Data Science, Workiva

• 10+ years in data science or machine learning roles
• Bachelor's degree in a quantitative field such as Computer Science, Statistics, Mathematics, or similar, with an advanced degree preferred
• Proven experience deploying machine learning models at scale in production environments

Desirable

• We are seeking a strategic, collaborative, and technically skilled Director of Data Science to lead and grow our data science team
• In this role, you will shape the team’s vision, foster an inclusive and high-performing culture, and drive impactful machine learning and advanced analytics initiatives across the organization
• You will work closely with cross-functional partners to address complex challenges and embed data science into our core products, services, and operations
• The role will report to the VP of Data & Analytics
• Define and lead the data science vision, strategy, and roadmap in alignment with business goals and measurable outcomes
• Act as a strategic advisor and thought leader, championing the adoption and responsible use of AI/ML across the organization
• Advocate for ethical, transparent, and compliant data use, upholding standards of fairness and accountability in all initiatives
• Build, mentor, and lead a high-performing, collaborative team of data scientists
• Foster a culture of inclusion, innovation, and continuous learning within the team
• Set clear goals and development plans to support team growth and success
• Partner closely with Sales, Product, Marketing, Customer Success, Engineering, and other teams to drive impactful data science initiatives
• Serve as a bridge between technical teams and business units, ensuring alignment on priorities, deliverables, and strategic value
• Translate complex, ambiguous problems into structured, actionable analytical solutions
• Deliver clear, compelling insights to both technical and non-technical audiences through storytelling and data visualization
• Present findings and strategic recommendations to senior and executive stakeholders to influence high-level decisions
• Oversee the full lifecycle of machine learning models, including development, validation, deployment, monitoring, and continuous improvement
• Collaborate with Data Engineering to design scalable, well-defined data assets, features, and metrics that support evolving analytical and product needs
• Establish and promote best practices in experimentation, modeling, data governance, and model reproducibility
• Ensure robust documentation, version control, and transparency across all projects to support sustainability and auditability
• Reliable internet access for any period of time working remotely, not in a Workiva office