What are the responsibilities and job description for the Manufacturing AI/ML Business Consultant position at Veridian Tech Solutions, Inc.?
Job Title : AI/ML Consultant (Background with Automotive Manufacturing Supplier/ Mes)
Location: Detroit, MI
Experience:
- 10 years of experience in business consulting, with at least 3 years focused on AI/ML solutions in manufacturing.
- Proven track record of delivering measurable results through AI/ML initiatives in the manufacturing sector.
We are seeking an experienced and innovative AI/ML Business Consultant with expertise in the manufacturing domain to drive digital transformation and operational excellence. The ideal candidate will have a deep understanding of manufacturing processes and the ability to identify, design, and implement AI/ML solutions that enhance productivity, reduce costs, and improve decision-making across the value chain.
Key Responsibilities:
- Strategic Advisory:
- Partner with manufacturing leaders to identify business challenges and opportunities that can be addressed using AI/ML solutions.
- Develop and present AI/ML strategies tailored to manufacturing operations, including production optimization, predictive maintenance, and quality control.
- Use Case Identification:
- Analyze manufacturing workflows, supply chain operations, and data sources to uncover AI/ML use cases such as process automation, demand forecasting, and defect detection.
- Assess feasibility and ROI of proposed solutions, aligning with business objectives.
- Solution Design & Implementation:
- Collaborate with technical teams to design AI/ML models for manufacturing-specific applications, ensuring scalability and reliability.
- Oversee the deployment and integration of AI/ML solutions into manufacturing systems, such as MES, SCADA, or ERP platforms.
- Data-Driven Decision Making:
- Leverage data analytics and AI to provide actionable insights that optimize production schedules, reduce downtime, and enhance operational efficiency.
- Drive adoption of predictive and prescriptive analytics for better decision-making.
- Stakeholder Engagement:
- Act as the liaison between business stakeholders and technical teams, ensuring clear communication and alignment on goals.
- Provide regular progress updates, insights, and recommendations to manufacturing leaders and executives.
- Change Management:
- Develop strategies to ensure smooth adoption of AI/ML solutions within manufacturing operations.
- Conduct workshops and training sessions to build organizational AI/ML literacy.
- Innovation & Continuous Improvement:
- Stay updated on the latest AI/ML trends, tools, and methodologies in manufacturing, such as IoT, digital twins, and edge computing.
- Benchmark AI/ML implementations against industry best practices and recommend continuous improvements.
Qualifications:
Education:
- Bachelor’s degree in Business, Industrial Engineering, Data Science, or a related field. A Master’s degree or MBA is preferred.
Skills & Expertise:
- Manufacturing Knowledge:
- In-depth understanding of manufacturing processes, including production planning, supply chain management, and quality assurance.
- Familiarity with manufacturing systems such as MES, ERP, and SCADA.
- AI/ML Expertise:
- Strong understanding of AI/ML concepts, tools, and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Experience with manufacturing-specific AI applications like predictive maintenance, defect detection, and process optimization.
- Data Analytics:
- Proficiency in data analysis and visualization tools such as Power BI, Tableau, or Qlik.
- Experience with big data and IoT platforms like AWS IoT, Azure IoT Hub, or Google Cloud IoT.
- Business Acumen:
- Ability to translate complex technical concepts into business language.
- Expertise in calculating ROI and presenting cost-benefit analyses to stakeholders.
- Collaboration & Communication:
- Strong communication and interpersonal skills to engage with technical and non-technical stakeholders.
- Demonstrated ability to lead cross-functional teams and drive project success.
Preferred Qualifications:
- Certifications in AI/ML (e.g., AWS Certified Machine Learning, Google Cloud ML Engineer).
- Experience with advanced manufacturing technologies like digital twins, robotics, and IoT.
- Knowledge of compliance standards and regulations in the manufacturing sector.