Data Science Summer Intern

Data Science Summer Intern at Experian

Experian is a global data and technology company dedicated to powering opportunities for individuals and businesses worldwide. Through our unique combination of data, analytics, and software, we redefine lending, prevent fraud, simplify healthcare, and create digital marketing solutions. Our mission extends to helping millions achieve financial goals and save time and money.

We operate across diverse markets, including financial services, healthcare, automotive, agrifinance, and insurance. Our commitment to innovation is reflected in our investments in people and advanced technologies, all to unlock the power of data.

The Experian Summer Internship Program

Rooted in our 'People First' philosophy, the Experian Summer Internship Program offers students across the country the chance to apply their education to real-world challenges through meaningful, hands-on projects. We are proudly named one of the Top 100 Internship Programs three years in a row, emphasizing our commitment to personal and professional development. Join us to explore your potential with a team invested in your growth.

About the Experian NA Innovation Lab

You will be an integral part of the Experian North America R&D Data Lab. This unit focuses on research and development of novel analytical solutions, new product prototyping, and the evaluation and acquisition of new data assets. This position requires a strong background in machine learning and data mining, with a preference for candidates experienced in analyzing large datasets and developing data-driven statistical models.

Responsibilities

• Create advanced machine learning analytical solutions to extract insights from diverse structured and unstructured data sources.
• Unearth data value by selecting and applying the right machine learning, deep learning, and processing techniques.
• Refine data manipulation and retrieval through the design of efficient data structures and storage solutions.
• Innovate with tools designed for data processing and information retrieval.
• Dissect and document vast datasets, analyzing and processing them to highlight patterns and insights.
• Solve complex challenges by developing impactful algorithms.
• Ensure model excellence by validating performance scores and analyzing ROI and benefits.
• Articulate model processes and outcomes, documenting and presenting findings and performance metrics.

Qualifications

• Return to school in the Fall of 2026 to complete degree program.
• Currently enrolled in a PhD degree program in Machine Learning, CS, Electrical Engineering, Physics, Statistics, Applied Math, or other quantitative fields.
• Experience in analytics, data mining, and/or predictive modeling.
• Experience modifying and applying advanced algorithms to address practical problems.
• Experience with deep learning (CNN, RNN, LSTM, attention models, etc.), machine learning methodologies (SVM, GLM, boosting, random forest, etc.), graph models, and/or reinforcement learning.
• Experience with open-source tools for deep learning and machine learning technology such as PyTorch, Keras, TensorFlow, scikit-learn, pandas.
• Experience with large data analysis using Spark (pySpark preferred).
• Proficient in more than one of Python, R, Java, C++, or C.

Benefits & Perks

• Fully remote work arrangement.
• Volunteer Time Off.
• Great compensation.
• Flexible work schedule.
• Eligible for 401(k) participation in 90 days.

Key skills/competency

• Machine Learning
• Deep Learning
• Data Mining
• Predictive Modeling
• Algorithm Development
• Spark (pySpark)
• Python
• TensorFlow
• Statistical Modeling
• Data Analysis