Chief Data Scientist

Location:

About the Role

Chief Data Scientist / Head of Data Science & Analytics

Key Responsibilities

• Leadership & Strategy

• Define and execute the organizations data science and AI strategy in alignment with business objectives.
• Lead cross-functional global teams of data scientists, data engineers, and analysts.
• Build and scale Centers of Excellence (CoEs) in supply chain analytics, AI/ML, and digital transformation.

• Business & Consulting

• Engage with

  C-level executives

   to shape analytics roadmaps, secure business opportunities, and drive adoption of AI-led solutions.
• Provide

  go-to-market consulting

   and develop data-driven business models to support growth.
• Drive multimillion-dollar analytics initiatives, ensuring ROI and measurable business impact.

• Technical Expertise

• Oversee development and deployment of

  predictive and prescriptive models

   for supply chain optimization, reliability engineering, and enterprise systems.
• Guide teams in designing scalable

  data platforms, dashboards, and visualization solutions

   for decision-making.
• Leverage expertise in

  big data analytics, machine learning, and optimization techniques

   to solve complex business challenges.

• Innovation & R&D

• Drive innovation in

  AI/ML, reliability engineering, and advanced optimization

   for next-gen solutions.
• Collaborate with academia and industry partners to explore emerging technologies, including

  Generative AI applications

  .
• Contribute to intellectual property, research publications, and technology patents where applicable.

• Ph.D. or Masters degree

   in Engineering, Data Science, Computer Science, Applied Mathematics, or related field.

• 20+ years of experience

   spanning engineering R&D, reliability, supply chain analytics, and data science.
• Proven track record in

  building and leading data science organizations

  , driving digital transformation, and securing large-scale business deals.
• Hands-on expertise in

  statistical modeling, predictive analytics, optimization techniques, and big data platforms

  .
• Strong background in

  hardware reliability engineering, system diagnostics, and product innovation

   (preferred for cross-domain leadership).
• Certifications in

  AI/ML, Generative AI, or Data Science

   (Coursera, LinkedIn, etc.) are a plus.

Required Qualifications

• Ph.D. or Masters degree

   in Engineering, Data Science, Computer Science, Applied Mathematics, or related field.

• 20+ years of experience

   spanning engineering R&D, reliability, supply chain analytics, and data science.
• Proven track record in

  building and leading data science organizations

  , driving digital transformation, and securing large-scale business deals.
• Hands-on expertise in

  statistical modeling, predictive analytics, optimization techniques, and big data platforms

  .
• Strong background in

  hardware reliability engineering, system diagnostics, and product innovation

   (preferred for cross-domain leadership).
• Certifications in

  AI/ML, Generative AI, or Data Science

   (Coursera, LinkedIn, etc.) are a plus.

Skills & Competencies

• Strategic Leadership

    ability to align AI/analytics initiatives with business priorities.

• Enterprise Consulting

   – experience engaging with global clients at VP & C-suite levels.

• People Leadership

   – team building, mentorship, and global workforce management.

• Technical Expertise

   – ML/AI, data engineering, visualization (Tableau, R/Shiny), optimization, reliability engineering.

• Entrepreneurial Mindset

   – experience in startup ecosystem and consulting leadership.