Data Science Summer Intern (Remote & Paid)

Position Overview

Experian is a global data and technology company that powers opportunities for people and businesses worldwide. As part of the Experian NA Innovation Lab – a dedicated R&D unit focused on enhancing client relationships and acquiring strategic datasets – you will join the North America R&D Data Lab. In this role, you will concentrate on research and development of novel analytical solutions, new product prototyping, and evaluating new data assets. A background in machine learning and data mining is essential, and previous experience analyzing large datasets and developing data-driven statistical models is highly desirable.

Key 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 by documenting and presenting findings and performance metrics

Required Qualifications

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

Benefits & Perks

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