Senior Supply Chain Data Science Strategist

22 hours ago

Solapur, Maharashtra, India beBeeSupplyChain Full time ₹ 40,00,000 - ₹ 50,00,000

Transform Supply Chain Operations through Data-Driven Excellence

Job Description:

As a senior professional, you will lead the strategic development and implementation of advanced analytics and AI solutions to enhance procurement, planning, and distribution processes. This role requires expertise in data strategy, AI/ML modeling, and team leadership.

Key Responsibilities:
  • Develop and execute comprehensive data science strategies to optimize supply chain operations, aligning with procurement and planning objectives.
  • Identify and integrate key data sources for enhanced visibility and accuracy in procurement decisions and planning & distribution processes.
  • Evaluate and implement emerging technologies (e.g., GenAI, IoT, digital twins) to enhance data collection, analysis, and visualization capabilities.
  • Collaborate with procurement and planning teams to prioritize data science initiatives driving operational efficiencies and cost savings.
Advanced Analytics and Modeling:
  • Deploy scientific replenishment strategies in Trade (India and Global markets).
  • Design and implement predictive AI/ML models for demand forecasting accuracy, inventory optimization, distribution planning, and supplier performance evaluation.
  • Explore and implement advanced analytics techniques, machine learning models, and AI algorithms to derive insights from large datasets.
  • Utilize machine learning algorithms to analyze historical data and inform procurement strategies and planning cycles.
  • Develop advanced analytics solutions to assess third-party manufacturer performance and optimize distribution logistics.
Team Leadership and Development:
  • Lead and mentor a team of data scientists, analysts, and AI experts fostering a culture of innovation and collaboration focused on supply chain challenges.
  • Set clear performance expectations and provide regular feedback to team members for professional development.
  • Encourage knowledge sharing and best practices within the team to enhance overall capabilities.
Performance Measurement and Reporting:
  • Develop KPIs to measure the impact of data science initiatives on supply chain performance.
  • Regularly report on project progress and outcomes to senior leadership and stakeholders, highlighting successes and areas for improvement.

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