Note: The job is a remote job and is open to candidates in USA. Bollinger Shipyards is seeking a Senior Manager, Data Science & AI to establish and scale enterprise artificial intelligence, machine learning, and advanced analytics capabilities. The role leads AI use-case prioritization, model development, governance, deployment, and integration while partnering with business and technical teams to improve forecasting, operational efficiency, planning, and decision-making.
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
Skills
- • 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
- • 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
Benefits
- 401k
- Dental Insurance
- Life Insurance
- Medical Insurance
- Vision
Company Overview