Supply Chain Data Scientist

HP•Spring, TX

2d•$147,050 - $232,850

About The Position

Supply Chain Data Scientist Description - HP is the world’s leading personal systems and printing company, dedicated to creating technology that enriches lives everywhere. Our innovation thrives on the passion, talent, and curiosity of our people—each bringing unique perspectives, expertise, and ideas to shape the future of how the world works and lives. Join HP’s Strategic Planning and Modeling (SPaM) Data Science Team – Where Vision Meets Impact Are you a visionary thinker with a passion for learning and innovation? Join our Strategic Planning and Modeling (SPaM) Data Science team, where we tackle complex supply chain challenges and drive strategic decision-making through advanced analytics. As a member of SPaM, you will: ✅ Evaluate supply chain investment and improvement opportunities. ✅ Develop cutting-edge predictive, prescriptive, and generative AI models to optimize business outcomes. ✅ Deliver strategic recommendations that shape HP’s global supply chain. ✅ Collaborate with senior executives to set direction and drive innovation. ✅ Lead with technical and analytical expertise to translate theory into impactful business solutions through strong execution and cross-functional orchestration. At SPaM, we bring over 35 years of supply chain innovation. We value flexibility, invest in your growth through formal training and mentorship, and foster a culture where creativity and data-driven insights power the future. If pioneering data-based innovations to transform HP’s supply chain excites you, we want to hear from you!

Requirements

MS/PhD in a business analytics field (i.e. Industrial Engineering, Management Science, Operations Research, Statistics, Data Science) or MBA with Supply Chain or Operations concentration
Operational experience in one of the following: inventory optimization, demand forecasting, network design, planning, forecasting, procurement, logistics, warranty, product quality, product variety management, or similar supply chain domain area
10+ years of experience
Expertise with inventory optimization math and deployment of the mathematical formulas into a business process
Applied experience with machine learning and optimization on large datasets
Proficient with Python, SQL, GitHub Co-Pilot, PowerBI, Excel
Experience with GenAI
Passion for data science & delivering data-driven outcomes
Demonstrated innovation across the supply chain domains (Plan, Source, Make, Deliver, Return)
Demonstrated practical experience in an operational environment
Experience implementing and handing off operational analytical solutions to business users
Demonstrated ability to deal well with ambiguity and work collaboratively in a fast-paced environment
Demonstrated ability to communicate concisely with diplomacy, credibility, and confidence
Experience with data visualization and data presentation in a clear and effective manner
Experience leading, collaborating with, and delivering results in cross-functional teams
Familiarity with statistics, forecasting, simulation, and spreadsheet modelling
A desire to be a part of the HP team with a commitment to build upon our brand that is synonymous with innovation, trust, reliability, and sustainability

Responsibilities

Collaborate & Strategize: Work closely with SPaM team members and cross-functional partners to define business challenges, develop analytical frameworks, gather key data, evaluate solutions, and deliver well-supported recommendations to leadership.
Drive Supply Chain Innovation: Develop and implement cutting-edge solutions in inventory management, working capital optimization, network design, forecasting, complexity reduction, product planning, manufacturing, and distribution to enhance efficiency and decision-making.
Transform Data into Impact: Leverage data visualization techniques to craft compelling narratives that communicate insights, drive action, and demonstrate business value.
Build & Scale Advanced Analytics Solutions: Design, deploy, and support predictive, prescriptive, and generative analytics models that drive measurable impact at scale.
Enable Change & Adoption: Apply proven change management strategies to facilitate smooth adoption of new analytics-driven solutions across the organization.
Stay Ahead of the Curve: Continuously enhance expertise in data science and supply chain management by staying informed on the latest advancements and industry trends.