Position SummaryThis role is not eligible for immigration sponsorship
Headquartered in Englewood Cliffs, N.J., Samsung Electronics America, Inc. (SEA), the U.S. Sales and Marketing subsidiary, is a leader in mobile technologies, consumer electronics, home appliances, enterprise solutions and networks systems. For more than four decades, Samsung has driven innovation, economic growth and workforce opportunity across the United States-investing over $100 billion and employing more than 20,000 people nationwide. By integrating our large portfolio of products, services and AI technology, we're creating smarter, sustainable and more connected experiences that empower people to live better. SEA is a wholly owned subsidiary of Samsung Electronics Co., Ltd. To learn more, visit Samsung.com. For the latest news, visit news.samsung.com/us.
Field service team is at the frontline of our home appliance service, dedicated to delivering the best customer experience by ensuring cx satisfaction & streamlining processes, and developing strategies for ongoing improvement and growth. Monitor KPIs, anaylze cx feedback and implement improvement using data insights. Collaborate with sales, other teams for seamless customer experience.
As an AI Engineering/Data Scientist Intern, you will support teams by participating in projects, observing professional work environments, and conducting research to contribute to the team's success.
Applying machine learning techniques to solve complex data problems
Utilizing natural language processing for data-driven insights
Engaging in predictive modeling to forecast trends and outcomes
Supporting data engineering projects with a focus on data quality and integrity
Role and Responsibilities- Programming: Python is essential (with libraries like NumPy, Pandas, Scikit-learn); SQL for data handling is also key; R, Java, C++ can be beneficial.
- Machine Learning: Understanding core ML concepts (supervised/unsupervised learning, regression, clustering) and algorithms.
- AI Frameworks: Experience with TensorFlow, PyTorch, or similar deep learning/AI libraries.
- Data Handling: Skills in data wrangling, cleaning, and using tools like Spark/Hadoop for large datasets.
- Mathematics/Statistics: Strong grasp of linear algebra, calculus, and statistics.
- AI Concepts: Familiarity with newer areas like LLMs, NLP, or Reinforcement Learning (RL) is a plus.
Skills and QualificationsAcademic Major Preferred: Master's
- Currently enrolled in a Bachelor's or Master's, Computer Science, Data Science, Statistics, Math, or a related quantitative field.
- Often a strong academic record (e.g., GPA 3.0+) is preferred.
- Preferred to have technical & professional experience.
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