Duncan Solutions

Data Scientist

• Define and lead the enterprise AI and data science strategy — aligned to Duncan's Enterprise Goals, corporate growth objectives, and the imperative to deliver client value through our products and services
• Advise the CTO and executive leadership team on opportunities to leverage artificial intelligence, machine learning, and predictive analytics to drive competitive advantage, margin improvement, and operational scale
• Translate strategic business priorities into high-impact data science programs with clearly defined financial and operational outcomes — not exploration for its own sake, but applied innovation with measurable returns
• Evaluate emerging technologies and industry trends to inform long-term digital strategy and investment decisions, bringing forward evidence-based recommendations rather than reactive responses to market noise
• Oversee the design, deployment, and scaling of advanced analytics solutions within AWS-native environments — supporting revenue optimization, compliance oversight, customer experience enhancement, and operational efficiency
• Champion automation and intelligent workflow transformation, including natural language processing, anomaly detection, and AI-driven operational optimization across Duncan's core service lines
• Ensure analytics solutions are production-ready, scalable, and maintained with the operational rigor expected of enterprise systems — not prototype-quality deliverables deployed into live environments
• Establish and maintain governance frameworks for model development, validation, monitoring, explainability, and ethical AI use — ensuring regulatory alignment and enterprise risk management at every stage of the analytics lifecycle
• Ensure responsible AI practices are embedded in team culture and delivery methodology — not treated as compliance overhead, but as a professional standard that protects both Duncan and the clients it serves
• Identify and surface emerging data science risks — model drift, data quality degradation, bias exposure, or governance gaps — before they become material issues for the enterprise or its clients
• Partner with Legal, Compliance, and the CTO on AI-related regulatory developments, ensuring Duncan's practices remain defensible, auditable, and ahead of evolving requirements
• Build and maintain executive-level dashboards and reporting frameworks that convert data science outputs into decision-enabling intelligence — giving the CTO, CEO, and enterprise leadership a clear, timely view of operational performance and AI-driven opportunity
• Ensure data science insights are communicated in plain, accessible language that enables non-technical leaders to act with confidence — translating model outputs into business narratives, not statistical summaries
• Support board-level reporting on AI strategy, innovation initiatives, and enterprise performance impact as directed by the CTO
• Recruit, develop, and retain high-performing data science and analytics professionals — building a team culture defined by accountability, intellectual rigor, and continuous improvement
• Establish clear performance expectations, development pathways, and capability-building investments aligned to Duncan's Job Group Family Architecture and the career development framework being built enterprise-wide
• Ensure the data science team operates as a trusted enterprise partner — responsive to business needs, disciplined in delivery, and consistent in the quality of its work
• Model the leadership behaviors Duncan expects at the senior leader level: operating with independence, developing the people around you, and connecting your team's daily work to the organization's long-term direction

Senior Director, Data Science