Supply Chain Planning Data Scientist

Job Overview

Location
Austin, Texas, United States
Job Type
Full Time

Additional Details

Job ID
6384
Job Views
31

Job Description

Note:

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HK Consultancy is a leading firm specializing in innovative supply chain solutions, committed to driving efficiency and sustainability across industries globally. We are seeking a talented Supply Chain Planning Data Scientist to join our dynamic team in revolutionizing supply chain strategies.

Job Summary:

As a Supply Chain Planning Data Scientist at HK Consultancy, you will play a pivotal role in leveraging advanced analytics and data-driven insights to optimize supply chain operations. You will collaborate closely with cross-functional teams to develop predictive models, enhance forecasting accuracy, and drive strategic decision-making processes.

Key Responsibilities:

  • Utilize statistical modeling and machine learning techniques to analyze complex data sets and derive actionable insights for supply chain optimization.
  • Develop and implement algorithms to improve demand forecasting, inventory management, and procurement strategies.
  • Collaborate with stakeholders to identify business requirements, formulate analytical approaches, and present findings to senior management.
  • Design and maintain data pipelines, ensuring data integrity and accessibility for ongoing analysis.
  • Stay abreast of industry trends and advancements in supply chain analytics to continuously innovate and improve processes.

Required Skills and Qualifications:

  • Advanced degree (Master or PhD) in Data Science, Operations Research, Statistics, Computer Science, or a related quantitative field.
  • Proven experience in applying statistical modeling, machine learning, and optimization techniques to real-world business problems, preferably within supply chain or logistics domains.
  • Proficiency in programming languages such as Python, R, or SQL for data manipulation and analysis.
  • Strong understanding of supply chain concepts and methodologies, including demand forecasting, inventory optimization, and logistics management.
  • Excellent communication skills with the ability to translate complex data findings into actionable insights for non-technical stakeholders.

Experience:

  • Minimum of 4 years of experience in data science or analytics roles, with a focus on supply chain planning and optimization.

Working Hours:

  • Standard working hours with flexibility required based on project needs.

Knowledge, Skills, and Abilities:

  • Deep analytical mindset with a passion for solving complex supply chain challenges through data-driven approaches.
  • Ability to work collaboratively in a team environment, effectively influencing and driving consensus across stakeholders.
  • Strong project management skills with the ability to prioritize tasks and deliver results within tight deadlines.

Benefits:

  • Competitive salary commensurate with experience.
  • Comprehensive benefits package including health insurance, retirement plans, and professional development opportunities.
  • Dynamic work environment fostering innovation and career growth.

Why Join HK Consultancy:

Join a visionary team at HK Consultancy dedicated to shaping the future of supply chain management through cutting-edge analytics and strategic insights. Collaborate with industry leaders and contribute to transformative projects that make a global impact.

How to Apply:

Interested candidates are encouraged to submit a resume and cover letter outlining their qualifications and experience relevant to the position of Supply Chain Planning Data Scientist at HK Consultancy. Please send your application to us.

Some Interview Points:

  • Prepare to discuss your experience with specific supply chain optimization projects and the methodologies you utilized.
  • Be ready to demonstrate your technical proficiency in statistical modeling and machine learning during the interview process.
  • Showcase your ability to communicate complex analytical findings to non-technical stakeholders effectively.

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