Supply Chain Analytics - Manager & Data Science

Supply Chain Operations domain and Data Science skills

Key Responsibilities

• Solution Architecture & Design

  :

  Solution architect, design, build, deploy, deliver, and monitor advanced analytics models

  tailored for critical supply chain planning areas (e.g., demand, supply, procurement, inventory, spares planning).

• Problem Translation

  : Interface directly with clients to thoroughly

  understand engineering/business problems

  and effectively

  translate them into actionable analytics problems

  that yield insightful, operational improvements.

• Client Engagement & Sales Support

  : Take initiative to

  collaborate with different Client internal teams and support driving sales

  by identifying opportunities where advanced analytics can add significant value.

• Innovation & Thought Leadership

  : Provide

  innovation and thought leadership support to build key capability areas

  , including:
• Identifying and evaluating new

  tools & technology

  relevant to supply chain analytics.
• Developing and piloting

  new solutions in supply chain planning

  .
• Contributing to

  assets & accelerators development

  to enhance delivery efficiency and scalability.

• Model Lifecycle Management

  : Manage the end-to-end lifecycle of analytics models, ensuring their accuracy, performance, and continuous improvement.

• Insight Generation

  : Deliver clear, concise, and actionable insights from data analysis to inform strategic and operational decisions.

Required Skills and Experience

• Expertise in

  Supply chain operations domain

  .
• Strong

  Data Science skills

  .
• Proven ability to

  solution architect, design, build, deploy, deliver, and monitor advanced analytics models for supply chain planning areas

  (e.g., demand, supply, procurement, inventory, spares, etc. planning).
• Demonstrated capability to

  interface with clients to understand engineering/business problems and translate them into analytics problems

  that deliver insights for action and operational improvements.
• Experience in taking initiatives and

  collaborating with different Client internal teams and supporting driving sales

  .
• Ability to provide

  innovation and thought leadership support to build key capability areas

  such as tools & technology, new solutions in supply chain planning, and assets & accelerators development.
• Proficiency in relevant data science tools and programming languages (e.g., Python, R, SQL, machine learning libraries).
• Strong analytical, problem-solving, and communication skills.