Supply Chain Principal Data Scientist

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Why Work at Lenovo

Here at Lenovo, we believe in smarter technology for all, so we spend our time building a society that’s brighter and more inclusive.

And we go big. No, not big—huge.

We’re not just a Fortune Global 500 company, we’re one of Fortune’s Most Admired. We’re in 180 markets, working with 63,000 brilliant colleagues and counting. And we’re known for the world’s most complete portfolio of smart technology, from devices to software to infrastructure.

With our ingenuity, we help millions—not just the select few—experience our version of a smarter future.

The one thing that’s missing? Well… you...

Description and Requirements

As a Principal Data Scientist, you will be responsible for:

• Work with the Analytics Director to define key questions and prioritize project work streams and initiatives that will transform the business and deliver business value
• Clearly understand the business requirements, objectives, and market before developing and implementing analysis strategies, tools, and solutions
• Develop, test, and deliver analytics solutions to enhance Lenovo’s supply chain operations via descriptive, predictive, and prescriptive analytics (through proof of concepts and enterprise grade solutions)
• Experience with large-scale algorithms extracting and analyzing data from multiple and complex data sets and ability to convert complex them into easy-to-understand insights and action plans
• Manage data science and analytics work streams working closely with internal teams together with colleagues within department and other Lenovo teams
• Present data-driven insights from multiple data sources (structured or unstructured) and help instill analytics solutions into day-to-day BMS in Supply chain functions for wider impact
• Researching and applying multidisciplinary techniques and tools, findings, algorithms, and approaches to solutions driving the business understanding of its market and data
• Building, validating, and prioritizing an analytics pipeline to improve demand plans, service levels, reduce inventory, optimize routing, and other supply chain KPI’s
• Work with analytics vendors especially in supply chain to build out capabilities in supply chain analytics and eventually migrate in house
• Collaborating with Data and IT teams and other internal groups to address data quality, master data management, data governance and metadata management goals and issues
• Assist with the talent and skill-set development of a multi-disciplinary team to become key decision influencers