Data Science Summer Intern

About Lensa

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About Experian

Experian is a global data and technology company committed to creating opportunities for individuals and businesses worldwide. We play a pivotal role in redefining lending practices, preventing fraud, streamlining healthcare, developing digital marketing solutions, and providing deep insights into the automotive market through our unique combination of data, analytics, and software. Additionally, we empower millions of people to achieve their financial goals, saving them time and money.

Our operations span various markets, including financial services, healthcare, automotive, agrifinance, insurance, and many other industry segments. We prioritize investment in our people and advanced technologies to unlock the full potential of data and foster innovation. Our focus on powering opportunities is exemplified by the Experian Summer Internship Program, which offers students nationwide the chance to apply their academic knowledge to real-world challenges through impactful, hands-on projects. Guided by our 'People First' philosophy, our interns gain firsthand experience of our dedication to their personal and professional growth. Having been recognized as one of the Top 100 Internship Programs for three consecutive years, we invite you to explore your potential with a team invested in your development.

As a FTSE 100 Index company listed on the London Stock Exchange (EXPN), Experian comprises a team of 25,500 people across 32 countries, with corporate headquarters located in Dublin, Ireland. You can learn more about us at experianplc.com.

About Experian NA Innovation Lab

The Experian NA Innovation Lab functions as a dedicated Research and Development (R&D) unit within Experian. Its primary objective is to collaborate with Experian's various teams to strengthen client relationships and acquire strategic datasets. Experian is a global leader in delivering information, analytical tools, and marketing services to organizations and consumers, helping them manage the risk and reward associated with commercial and financial decisions. By leveraging our comprehensive understanding of individuals, markets, and economies, we assist organizations in managing customer relationships to enhance their business profitability.

As a Data Science Summer Intern, you will be an integral part of the Experian North America R&D Data Lab, focusing on the 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 and knowledge in machine learning and data mining. Previous experience in analyzing large datasets and developing data-driven statistical models is highly desirable.

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 specifically 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, thoroughly documenting and presenting findings and performance metrics.

Qualifications

• Must 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 other quantitative fields.
• Experience in analytics, data mining, and/or predictive modeling.
• Experience modifying and applying advanced algorithms to address practical problems.
• Proficiency with deep learning techniques (e.g., CNN, RNN, LSTM, attention models), machine learning methodologies (e.g., SVM, GLM, boosting, random forest), 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, or 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.

Experian Culture

At Experian, our unique people and culture truly distinguish us. We are deeply committed to fostering an environment where everyone feels a sense of belonging and can truly excel. We focus on what truly matters, from promoting inclusion and authenticity to ensuring work/life balance, facilitating professional development, supporting wellness, encouraging collaboration, and recognizing achievements. Our 'people-first' approach has garnered global recognition, including being named one of the World's Best Workplaces™ 2024 (Fortune Top 25), Great Place To Work™ 2025 in 26 countries, and Glassdoor Best Places to Work 2024, among other accolades.

To get a true sense of life at Experian, we invite you to explore Experian Life on social media or visit our Careers Site.

Compensation Information

Our compensation structure reflects the cost of labor across various U.S. geographic markets. The hourly pay range for this position, while not explicitly stated here, is determined by factors such as work location, job-related skills, experience, and educational background.

Equal Opportunity Employer

Experian proudly operates as an Equal Opportunity Employer, protecting all groups under applicable federal, state, and local law, including protected veterans and individuals with disabilities. Should you require any accommodation due to a disability or special need, please inform us at your earliest convenience.

Key skills/competency

• Machine Learning
• Deep Learning
• Data Mining
• Predictive Modeling
• Algorithm Development
• Spark (PySpark)
• Python/R Programming
• Statistical Modeling
• Big Data Analysis
• Data Structures