Senior Data Scientist
Montana State Fund Helena, Montana, United States
Insurance · 201-500 employees
About the role
The Senior Data Scientist will lead the design and implementation of complex technical solutions, integrating AI-driven analytics and predictive modeling into enterprise systems. They will oversee end-to-end project lifecycles while collaborating with cross-functional teams to deliver secure, scalable, and data-driven business outcomes.
What they look for
Requirements
Candidates are expected to provide high-level technical leadership and possess expertise in developing models using scientific, mathematical, and machine-learning techniques. The role requires experience in project management, system modernization, and the ability to mentor IT and business professionals.
Full description
This posting is scheduled to close on September 23, 2026. If a sufficient number of qualified applications are received, this posting may close early. Apply today!
Required Application Documents:
- Resume
- Cover Letter
About the Job:
Montana State Fund (MSF) is seeking a Senior Data Scientist who will lead the design and implementation of complex technical solutions that support MSF’s business applications, data systems, and advanced analytics. In this role, you will provide high‑level technical leadership, evaluate and modernize existing systems, and integrate emerging technologies, including AI‑driven analytics and predictive modeling, into enterprise platforms. You will collaborate with engineers, analysts, and business partners to deliver secure, scalable solutions that strengthen MSF’s technical capabilities and support mission‑critical decision making
Key responsibilities include:
- Enterprise Technical Leadership: Provide high‑level technical leadership for advanced insurance, data, and analytics solutions; lead design and development across complex enterprise projects and platforms. Integrate emerging technologies, including AI‑driven analytics, predictive modeling frameworks, and natural‑language‑based solutions, into MSF applications and enterprise systems.
- Architecture, Engineering, and Solution Design: Analyze, design, and develop system artifacts consistent with best practices, enterprise standards, and architectural specifications. Evaluate existing systems built on MSF technologies, identifying opportunities for modernization, automation, and AI‑enhanced performance improvements. Lead the development of models and analytical solutions using scientific, mathematical, and machine‑learning techniques to predict outcomes, assess risk, and support strategic decision‑making.
- Project & Program Leadership: Lead matrixed project teams composed of business SMEs, engineers, analysts, and offshore/onshore development partners. Oversee end‑to‑end project lifecycle activities including planning, requirements analysis, sprint management, execution, risk mitigation, and status reporting. Incorporate agile methodologies and project management best practices to ensure timely delivery of high‑quality, secure, and scalable solutions.
- Data Engineering & Advanced Analytics: Design and implement predictive models, statistical frameworks, automated decision engines, and data pipelines to generate actionable insights for enterprise stakeholders. Build, refine, and operationalize NLP‑based tools for text classification, claims interpretation, and enhanced customer‑service automation.
- Mentorship, Collaboration & Communication: Provide technical expertise and mentoring to IT and business professionals, supporting continuous improvement and innovation across MSF. Communicate technology opportunities, risks, and project status to stakeholders at multiple levels of the organization.
Additional functions:
- Lead large, complex projects that include both onsite and remote business/technical teams.
- Prepare technical reports, project specifications, and documentation supporting design decisions, system
- Support user training and adoption of newly developed analytic tools, AI engines, and system enhancements.
- Store, retrieve, and manipulate data to drive continuous improvement in enterprise analytics and predictive capabilities.
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