Ph.D. in Data Science

This Program Is Available: On Campus

Apply Now

Artificial intelligence is the hottest topic in business and science, yet there’s a shortage of thought leaders capable of studying, understanding and applying advances in A.I. and machine learning in practical ways.

At Stevens, the interdisciplinary Ph.D. in Data Science prepares inquisitive students to become pioneers in this space through a rigorous curriculum emphasizing mathematical and statistical modeling, machine learning, computational systems and data management. The program is administered through both the Schaefer School of Engineering and Science and the School of Business at Stevens, ensuring a diverse curriculum that responds to demand for data scientists with extensive knowledge of the theories, techniques and applications associated with data and artificial intelligence. Graduates become research leaders in academia or industry, where they lead the organization’s forays through the data revolution and into the age of A.I. and machine learning.

Who should apply

Curriculum overview

Hanlon Financial Systems Center

'America's Hottest Job'

Bloomberg explains how top companies in the U.S. and beyond are aggressively competing for data scientists who can turn social media posts into monetizable binary code.

Bloomberg on data science

Research report 2017: Creating impact

The 2017 research report for the School of Business highlights the areas in which faculty are creating meaningful impact in a business world transformed by digital- and data-driven innovations.

2017 research summary

A unique blueprint for aspiring data scientists

Given the rapid evolution of emerging A.I. concepts like machine learning and language processing, Stevens worked with industry to develop four curricular threads that ensure mastery of the most important principles in this discipline. These areas represent the greatest needs for tomorrow’s data scientist.

Machine learning and artificial intelligence. Explores statistical learning, A.I., machine learning and financial analytics.
Mathematical and statistical modeling. Covers multivariate analytics, financial time series and dynamic programming techniques.
Computational systems. Explores advanced algorithm design, distributed systems and cloud technologies.
Data management at scale. A deeper dive into data technologies, mobile systems and data management.

Data Science faculty

As a Data Science student, you'll work closely with faculty whose research is responsible for important breakthroughs in artificial intelligence, deep learning, computational intelligence and more.

Dr. Dave Belanger with the New York skyline in the background.

David Belanger

A former chief scientist at AT&T Labs, Dr. Belanger has earned more than 30 patents related to data science and business analytics.

Germán Creamer

A highly cited business researcher investigating applications of machine learning and social network algorithms to solve finance problems.

Ionut Florescu

Dr. Florescu is an expert in creating stochastic models for practical application. He leads an international conference on high frequency in finance.

Ted Lappas

An expert in data mining and deep learning, Dr. Lappas is an authority in the business impact of fake reviews in social media.

Talking fake reviews with NBC News More on Dr. Lappas

Jeff Nickerson against the New York City skyline.

Jeffrey Nickerson

Dr. Nickerson has won many grants from NSF to explore crowd creativity, collective intelligence and information systems design.

Machines that Augment Workers More on Dr. Nickerson

Antonio Nicolosi

Dr. Nicolosi is an accomplished researcher whose work in cryptography and security in distributed systems is breaking new ground in data science.

Steve Yang

Dr. Yang's work in systemic risk, fraud detection and behavioral finance is changing how companies operate in the finance space.

Modeling markets More on Dr. Yang

Doctoral concentrations

Students in the Data Science program choose one of the available concentrations or, working closely with their faculty advisor, create a custom concentration of their own.

Financial services

The data-driven disruption in finance continues to be the story of the industry. Topics covered in this concentration are focused on creating opportunities in robo-advising, financial innovation, portfolio optimization, fraud detection and beyond through careful study of topics like data visualization and analytics, machine learning, natural language processing and text mining.

Financial Services curriculum

A spooky skeleton with some data projected on a screen.

Life sciences

The use of data science techniques is increasingly helping researchers unlock new discoveries in the traditional sciences. This concentration prepares you to solve problems through analysis of experimental, drug performance and patient data and techniques such as statistical modeling, data management and machine learning.

Life Sciences curriculum

High-tech labs power impactful research

To be a thought leader in data science, you must be an excellent researcher. At Stevens, you'll work in high-tech labs and with faculty in world-renowned centers to prepare you for career success.

A professor points to a touchscreen display showing financial data in the lab.

An edge in fintech

The Hanlon Financial Systems Center's two labs offer unrivaled financial analytics and data visualization capabilities.

Inside the Hanlon Center

A starburst at the convergence of threads of data.

Institute for A.I.

The Stevens Institute for Artificial Intelligence is the hub connecting dozens of researchers investigating A.I. and machine learning.

Powering A.I. research at Stevens

Health and A.I.

The Health and A.I. Laboratory aims to improve human health through the development of artificial intelligence methods.

Inside HAIL

Bio boost

Work at the Computational Systems Biology Lab involves modeling biological systems in the study of complex systems with diverse elements.

Inside the center

Contact Us