Senior Manager Data Science & AI

LED FastStart•Raceland, LA

2d•Remote

About The Position

The Senior Manager, Data Science & AI is responsible for establishing and scaling enterprise artificial intelligence, machine learning, and advanced analytics capabilities across Bollinger Shipyards. This role leads the identification, prioritization, development, and operationalization of AI solutions that improve forecasting, bidding, operational efficiency, planning, and decision-making. The role partners closely with business leaders, Data Engineering, Analytics, and Enterprise Architecture to ensure AI initiatives are aligned to strategic priorities and successfully integrated into enterprise operations.

Requirements

Bachelor’s degree in Data Science, Computer Science, Statistics, Engineering, Mathematics, or related field
8+ years of experience in data science, AI, machine learning, or advanced analytics roles
3+ years of leadership experience
Proven experience leading enterprise AI and ML initiatives from concept through operational deployment
Strong background in statistical modeling, machine learning, predictive analytics, and optimization techniques
Experience working with large and complex enterprise datasets
Experience leading technical teams and enterprise-scale initiatives

Nice To Haves

Experience in manufacturing, industrial, shipbuilding, engineering, or operational environments
Experience with Azure AI, ML Ops, cloud AI platforms, and modern AI frameworks
Familiarity with Generative AI, intelligent automation, and agent-based AI applications
Experience operationalizing AI solutions within ERP or operational systems
Knowledge of AI governance, model risk management, and responsible AI practices

Responsibilities

Define and execute the enterprise roadmap for AI, machine learning, and advanced analytics initiatives
Identify and prioritize high-value AI and predictive analytics use cases aligned to operational and strategic objectives
Lead development of models supporting forecasting, cost estimation, scheduling, bidding optimization, operational efficiency, and intelligent automation
Establish standards and governance for model development, validation, deployment, monitoring, and lifecycle management
Ensure AI and ML solutions are integrated into enterprise workflows and production systems
Partner with Data Engineering teams to ensure availability of scalable, high-quality datasets for model development
Collaborate with business leaders to drive adoption and measurable business value from AI capabilities
Evaluate emerging AI technologies, platforms, and opportunities relevant to Bollinger’s operational environment
Lead and develop data science and ML engineering resources
Ensure responsible, secure, and compliant use of AI technologies and enterprise data
Establish KPIs and performance measures for AI initiatives and operational impact