Supply Chain Analytics Intern (AI/ML)

Samsung Electronics•Englewood Cliffs, NJ

1d•$36 - $41•Onsite

About The Position

Samsung Electronics America is seeking a highly motivated, detail-oriented, and analytical Supply Chain Analytics Intern (AI/ML) to support the development and implementation of data-driven solutions for optimizing supply chain operations. This role is integral to enhancing Samsung's supply chain efficiency, improving demand forecasting, and ensuring timely delivery of products to meet customer needs. The intern will work with large datasets to model key performance indicators (KPIs) and value-driving metrics, leveraging advanced analytics, artificial intelligence (AI), and machine learning (ML) techniques. The intern will collaborate with cross-functional teams, including supply chain, operations, and data science, to analyze and interpret complex data sets. The primary focus will be on developing predictive models and actionable insights to improve supply chain processes, reduce costs, and enhance customer satisfaction. This role offers a unique opportunity to work on high-impact projects that shape Samsung's supply chain strategy while gaining hands-on experience in cutting-edge technologies and methodologies.

Requirements

Education: Master's degree in Statistics, Computer Science (specializing in Data Analytics or AI & Machine Learning), or Data Science. Final year or recent graduates strongly preferred.
Skills: Ability to quickly learn new tools, technologies, and methodologies.
Strong analytical mindset with the ability to tackle complex problems and develop effective solutions.
Proficiency in analyzing large datasets to derive actionable insights.
Experience with data visualization tools (preferred Tableau due to company policy).
Ability to develop and implement statistical and machine learning models.
Foundations in basic ETL (Extract, Transform, Load) setup.
Basic database management concepts.
Proficiency in Python for data analysis and modeling.
Soft Skills: Strong communication skills with the ability to present complex data insights in a clear and concise manner.
Ability to work effectively with cross-functional teams, including supply chain, operations, and data science teams.
Ensuring accuracy and consistency in data analysis and reporting.

Responsibilities

Retrieve and source relevant data from various internal and external sources to support supply chain analytics projects.
Clean, preprocess, and aggregate large datasets to ensure accuracy and consistency for analysis.
Develop and implement statistical and machine learning models to analyze key supply chain metrics, including:
Forecast revenue based on historical data, market trends, and other relevant factors.
Analyze inventory aging to identify potential risks and optimize stock levels.
Monitor and improve the timeliness of product shipments.
Identify inefficiencies in cross-shipping processes and develop predictive models to mitigate risks.
Analyze regional and seasonal trends to optimize product distribution and marketing strategies.
Study the impact of pricing on demand and develop strategies to manage price volatility.
Predict vendor sell-out rates to improve supply chain planning and inventory management.
Create clear and insightful visualizations using tools like Tableau (preferred due to company policy) to communicate findings to stakeholders.
Work closely with cross-functional teams, including supply chain, operations, and data science, to ensure alignment and successful project execution.
Prepare detailed reports and presentations summarizing findings, recommendations, and next steps for leadership review.