• 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.