Data Science Summer Intern (Remote & Paid)

Experian•Madison, MS

8d•$45 - $55•Remote

About The Position

Experian NA Innovation Lab is a R&D unit at Experian formed with the desire to work in collaboration with Experian's teams to enhance relationships with clients and acquire strategic datasets. Experian® is a global leader in providing information, analytical tools and marketing services to organizations and consumers to help manage the risk and reward of commercial and financial decisions. Using our comprehensive understanding of individuals, markets and economies, we help organizations manage customer relationships to make their businesses more profitable. You will be part of the Experian North America R&D Data Lab concentrating on research and development of novel analytical solutions, new product prototyping, and new data asset evaluation and acquisition. This position requires background and knowledge in machine learning and data mining. Previous experience analyzing large datasets and developing data-driven statistical models is desirable.

Requirements

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

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