Supply Chain Data Scientist

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Data Scientist within Global Logistics (GLO) Organization that supports Intel's Supply Chain.
The ideal candidate will be inquisitive, motivated and have a strong affinity to data with proven experience in delivering analytics and data solutions within the supply chain domain.
Data Scientist will be responsible for: Development of advanced analytics and AI solutions for Logistics Cross Border Optimization COE (center of excellence) Tariff assessment focusing on pre-entry and post entry reviews.
Analyzing customs data, and HTS data into actionable insights through data modeling, automation, predictive analytics, and intelligent decision-support tools.
Key Analytical functions include: Creation of Tariff forecasts, monthly spending reconciliation, understanding spending drivers and leading cost savings initiatives.
Identify improvements based on thorough understanding of business processes and supply chain dependencies.
Must possess high tolerance of ambiguity and ability to properly prioritize workload, ability to work on multiple projects simultaneously, manage stakeholders, analysis, benchmarking and system enhancements.

The ideal candidate should exhibit the following behavioral traits: Possess strong written and communication skills.
Self-starter, responsible, dependable, inquisitive and possess a desire to drive change and infuse new mindset to streamline business.
Challenges status quo and has a passion to drive smart change using data.
Qualifications Possess a Bachelor’s or Master’s Degree in Business Analytics, Operations Research, Statistics, Computer Science / Machine Learning or Supply Chain Management.
Experienced supply chain background (1-2 years) in transportation and/or warehousing.
Strong analytical and data mining skills including proficiency with Excel, SQL, Access, Python and Power BI.
Proficient with advanced analytics to find patterns and relationships in data, create data models and visualizations to tell a compelling story, and interpret the results that will enable others to drive change.
Proficient with predictive modeling, statistics, Machine Learning, Data Mining, and other data analysis techniques to collect, explore, and extract insights from structure and unstructured data.
Proficient with scripting languages (i.e.
Python, Perl),Advanced Analytics, HANA, HADOOP, and other data science and analytics emerging trends.
Ability to communicate effectively and solve difficult problems with effective solutions.
Proven success in fast-paced projects, analysis capabilities, high initiative and creativity.

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