Textron Specialized Vehicles Inc. is a leading global manufacturer of golf cars, utility and personal transportation vehicles, professional turf-care equipment, and ground support equipment. Textron Specialized Vehicles markets products under several different brands. Its vehicles are found in environments ranging from golf courses to factories, airports to planned communities, and theme parks to hunting preserves. 

Responsibilities:

 

• Leads the translation of business objectives into analytics and AI use cases by defining problem statements, success metrics, scope boundaries, and key assumptions in partnership with stakeholders.
   
• Conducts data acquisition, exploration, and readiness assessments to evaluate source suitability, data quality, and coverage; documents findings and risks to inform solution feasibility and approach.
   
• Designs, develops, and validates statistical, machine learning, and AI models using iterative experimentation and appropriate evaluation methods to ensure fitness for intended use.
   
• Partners cross-functionally with engineering, product, and platform teams to support implementation of models and analytics capabilities into operational processes and/or products.
   
• Establishes and maintains performance monitoring practices for production solutions, including accuracy tracking and operational reporting to support continuous improvement and reliability.
   
• Develops and standardizes reusable analytics assets (e.g., frameworks, processes, tools, and documentation) that improve consistency, scalability, and time-to-value across analytics initiatives.
   
• Communicates analytical results and recommendations to diverse audiences through clear narratives, visualizations, and decision-ready reporting to enable informed action.
   
• Ensures solutions align with enterprise governance and risk expectations by supporting approved data usage, controlled deployment practices, and appropriate documentation throughout the solution lifecycle.
   
• Provides technical leadership and mentorship by coaching peers and junior team members, promoting best practices, and contributing to capability building across the organization.

• Education: Bachelor's degree in Data Science & Analytics, Engineering, Mathematics, Industrial Engineering, Computer Science, Economics/Finance, Statistics, Applied Statistics, or Operations Research required.
  Advanced degree, M.B.A, or professional certification in Data Science & Analytics preferred.
• Years of Experience: 10 + years of professional experience required. Experience working with predictive analytics and/or electric vehicles preferred.
• Software Knowledge: 
  • Proficiency in data science and analytics programming languages such as Python and/or R, with strong SQL skills for querying, transforming, and analyzing structured enterprise data to support advanced analytics, modeling, and AI use cases is required.
  • Experience with data visualization and business intelligence tools such as Power BI (or comparable platforms) to develop dashboards, reports, and visual narratives that communicate analytical results and decision-ready insights to technical and non-technical stakeholders is required.
  • Preferred experience working with SAP data, including transactional, master, or analytical datasets, to support enterprise reporting, analytics, and predictive modeling use-cases.
  • Preferred experience working with Salesforce data, such as CRM objects or operational datasets, to enable analytics, insights, and data-driven decision support across business functions.
• Additional Requirements: 
  • Strong analytical and problem-solving skills, with the ability to evaluate ambiguous problems, assess feasibility, and recommend data-driven approaches aligned to business objectives.
  • Demonstrated ability to collaborate cross-functionally with business, engineering, and IT partners to deliver analytics and AI solutions in enterprise environments.
  • Effective written and verbal communication skills, including the ability to explain technical concepts and analytical findings to non-technical audiences.
  • Experience working within governed, security-conscious organizations, with an understanding of data privacy, access controls, and documentation expectations.
  • Ability to manage multiple priorities and deliver work independently, while maintaining attention to detail and meeting agreed timelines.