Report To: VP of Engineering I Department: Engineering Team I Location: Pasadena, CA I Duration: 10 - 12 Weeks (start and end date is determined by academic calendar)

Why You'll Love Interning Here:

• Strong track record of providing an inclusive culture of belonging and empowerment in an entrepreneurial environment.
• Gain real world experiences and become more marketable as you partner with the very best minds in our industry.
• Flexible schedules and work-from-home opportunities; casual dress environment.

What You'll Be Doing:

Supplyframe, a Siemens company, is an innovative and rapidly growing leader in the electronics component industry. We are currently recruiting students to kick off our Summer 2025 Internship Program.

We are seeking a talented and driven Data Scientist Intern to join our team! The role will focus on analyzing large-scale e-commerce data to identify key trends, uncover patterns, and solve complex problems. You will work on projects that involve traffic analysis, user behavior modeling, and predictive analytics using machine learning techniques. The ideal candidate will have a passion for applying machine learning algorithms to extract insights and turning data into actionable recommendations to improve performance and drive business decisions.

Our goal is to empower our students to become the next generation of leaders at our company!

Who/What We Are Looking For:

• Actively enrolled as a university student and in pursuit of a PhD or Master's Degree in Statistics, Data Science, Machine Learning or related quantitative discipline.
• Actual work experiences in training machine learning models and python programming.
• Passion for solving real-world problems on web analytics with user log data.

Preferred, But Not Required:

• Experience with Hadoop/Spark/Scala.
• Experience in research and a proven track record of solving end-to-end problems, from formulating research questions to implementing practical solutions.

The hourly range for this position is $43.27 to $48.08. The actual compensation offered is based on the successful candidate's work location as well as additional factors, including job-related skills, experience, and relevant education/training.

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