Textron Specialized Vehicles Inc. is a leading global manufacturer of golf cars, utility and personal transportation vehicles, 
snowmobiles, side-by-sides, all-terrain 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:

• Build best-in-class predictive and prescriptive models considering business constraints.
• Perform data integration, data set cleansing, and data analysis, and deploy analytical models through the 
  development of scripts and custom workflows.
• Monitor the performance and accuracy of existing models.
• Advise IT Data Engineers to build, automate, and/or maintain a set of enterprise-wide data services (data lake) and 
  connectors for internal and external data sources that can be rapidly deployed to business analysts.
• Create proactive and reactive custom reports based on client needs.
• Troubleshoot issues, prepare summaries, document processes and workflows, propose solutions, and collaborate and 
  communicate with internal team members.
• Build and maintain trusted relationships with information managers, architects, and business units for knowledge 
  sharing, mentoring, and training.
• Generate and effectively communicate analytical insights through visualization and reporting tools such as SAS, JMP,
  MS PowerBI, HANA, Qlik, and R Markdown.
• Research, evaluate and implement emerging trends in AI/ML space and published state-of-the-art ML methods,
  technologies, and frameworks.

Qualifications:

• Education: Bachelor's degree in Data Science & Analytics, Engineering, Mathematics, Industrial Engineering,
  Computer Science, Information Technology, Economics/Finance, Statistics, Applied Statistics, or Operations Research
  required; Professional certification in Data Science & Analytics preferred
• Years of Experience: P2: 3 or more years of experience required; P3: 5 or more years of experience required,
  experience in stochastic process modeling, design of experiments, non-linear regression, simulation, and optimization 
  methods; experience developing AI and Machine Learning solutions, from concept to production, and selecting the 
  right algorithm/approach for the job at hand
• Software Knowledge: Proficiency in data science object-oriented programming languages (python, R, ruby), and 
  proficiency in database languages (MSSQL, Oracle, PostgreSQL, MySQL, neo4j, HANA, Hadoop
• Familiar with Natural Language algorithms for processing/generation (NLP/NLG) and with available open source 
  AI/ML platforms, especially in deep learning/neural network space.