M.B.A. in Business Administration
The Stevens MBA program offers various formats to cater to diverse student needs, inclu...
M.S. in Data Science
Hoboken, New Jersey
INTAKE: Jan & Sept
Program Overview
The M.S. in Data Science is a 30-credit program, typically completed within 1.5 to 2 years, available in both on-campus and fully online formats for maximum flexibility. The curriculum is structured around five core courses (15 credits) that establish a comprehensive theoretical and methodological framework, complemented by five elective courses (15 credits). This allows students to tailor their learning experience towards specific career paths, with optional concentrations in areas such as Fundamentals of Data Science, Data Acquisition and Management, Data Security, and Business Applications. Students also have the option to complete a 6-credit master's thesis for those interested in a research-intensive path.
STEM-designated: Yes, the Stevens Institute of Technology M.S. in Data Science program is STEM-designated. This is a significant advantage, particularly for international students. The STEM designation makes them eligible for a 24-month extension of their Optional Practical Training (OPT) in the United States, allowing for a total of up to three years of valuable post-graduation work experience. This designation underscores the program's strong quantitative, mathematical, and computational focus, which is highly valued by employers in the data science and technology sectors.
Curriculum: The 30-credit curriculum builds a strong foundation in data science principles. Core courses typically include Statistical Methods, Applied Machine Learning, Deep Learning, Optimization for Data Science, and Numerical Linear Algebra for Big Data. Elective courses offer in-depth study in specialized areas such as Time Series Analysis, Statistical Network Analysis, Spatial and Spatio-Temporal Statistical Modeling, Tensor Methods for Data Analysis, Introduction to Network and Graph Theory, Stochastic Processes, Advanced Optimization Methods, Topological Data Analysis, Dynamic Programming and Reinforcement Learning, Natural Language Processing, and various cybersecurity-related courses. The program emphasizes hands-on proficiency with industry-standard tools and languages like Python, R, SQL, Hadoop, Hive, and TensorFlow.
Research Focus: The M.S. in Data Science program at Stevens has a strong applied research focus, emphasizing the exploration, analysis, and modeling of data to tackle real-world challenges. The curriculum is designed to equip students with the ability to construct new relevant models and design algorithms tailored for challenging real-life situations, interpret model outputs, and make relevant decisions. Faculty members are actively engaged in cutting-edge research across various aspects of data science, including machine learning, deep learning, statistical modeling, and data security. The option to complete a 6-credit master's thesis allows students to engage in a specific research project under faculty mentorship, contributing to the field's advancements.
Industry Engagement: Stevens Institute of Technology places a very high priority on industry engagement for its Data Science program. Its strategic location in Hoboken, just minutes from downtown Manhattan, provides unparalleled access to leading tech companies, financial institutions, and data-driven businesses. The program's curriculum is constantly updated to reflect the latest industry demands, ensuring graduates possess in-demand skills in areas like machine learning, predictive modeling, and data visualization. Stevens boasts exceptional career outcomes for its data science graduates, with 97% employed within three months of graduation and a high average compensation. The university actively facilitates connections between students and employers through career services, networking events, and a powerful alumni network, positioning graduates for success in a high-demand field.
Global Perspective: Stevens Institute of Technology fosters a global perspective within its M.S. in Data Science program through its diverse international student body and the universal applicability of data science principles. The program attracts students from various countries, creating a rich multicultural learning environment that broadens perspectives on global data challenges and ethical considerations. The skills learned, from managing large-scale data to applying advanced analytical techniques, are highly transferable across international markets and industries. This global outlook, coupled with the program's robust technical foundation, prepares graduates to contribute to data-driven innovation and problem-solving on an international scale.
Location
Hoboken, New Jersey
Score
IELTS 6.5
Tuition Fee
USD 46048
Postgraduate Entry Requirements
Academic Qualifications: Applicants for postgraduate programs typically require a minimum academic achievement of 70% or above in their bachelor's degree.
English Language Proficiency:
- IELTS: Overall band score of 6.5 or 7.0 with a minimum of 6.0 in each component.
- TOEFL: Overall score of 74 or higher.
- DET (Duolingo English Test): Minimum score of 110.
Stevens Institute of Technology offers a variety of scholarships specifically designed to support international students, helping to make a world-class education more affordable and accessible. These scholarships recognize academic excellence, leadership potential, and contributions to the campus community.
Merit-Based Scholarships: Stevens provides competitive merit scholarships for international undergraduate and graduate students based on academic performance, standardized test scores, and other achievements. These awards can significantly reduce tuition costs and are automatically considered during the admissions process for many programs.
Need-Based Financial Aid: While limited, some need-based aid options are available to international students. Applicants are encouraged to provide detailed financial information to be considered for such assistance.
Graduate Fellowships and Assistantships: International graduate students may be eligible for fellowships, research assistantships, or teaching assistantships, which offer tuition waivers and stipends. These opportunities not only provide financial support but also valuable hands-on experience in research and academic work.
Special Scholarships: Stevens occasionally offers specialized scholarships targeting students from certain countries, underrepresented fields, or those pursuing specific disciplines like engineering, business, or cybersecurity. Prospective students should check the official Stevens website or contact the admissions office for current scholarship opportunities.
A Master of Science (M.S.) in Data Science from Stevens Institute of Technology, located in Hoboken, New Jersey, is a highly distinguished and STEM-designated program that prepares graduates for crucial roles in the data-driven world.
Data Scientist: This is the most direct career path, involving the collection, cleaning, analysis, and interpretation of large, complex datasets. Graduates build predictive models, extract actionable insights, and communicate findings to drive data-driven decision-making across various industries like tech, finance, healthcare, and e-commerce.
Machine Learning Engineer: Leveraging their expertise in machine learning and deep learning, graduates design, develop, and deploy machine learning models. They focus on building intelligent systems, optimizing algorithms, and integrating AI capabilities into products and services.
Data Engineer: These professionals are responsible for designing, building, and maintaining robust data pipelines and infrastructure. They ensure that data is collected, stored, processed, and made accessible for data scientists and analysts, often working with big data technologies like Hadoop and Hive.
Business Intelligence (BI) Analyst/Developer: Graduates analyze business data to create meaningful insights, dashboards, and reports that help organizations understand their performance, identify trends, and make informed strategic and operational decisions.
Quantitative Analyst (Quant): With a strong emphasis on statistical modeling and numerical methods, graduates are well-suited for roles in financial institutions. They develop complex mathematical models for pricing financial instruments, managing risk, and devising trading strategies.
Applied Research Scientist (Data Science): For those interested in pushing the boundaries of data science, this role involves conducting research to develop new algorithms, methodologies, and applications of data science in various domains, often within corporate R&D labs or academic settings.
Analytics Consultant: Graduates can work for consulting firms, advising diverse clients on how to leverage their data to improve business processes, optimize strategies, and solve complex problems through data analysis and predictive modeling.
Statistical Modeler/Statistician: Specializing in statistical methods and inference, graduates design experiments, analyze data, and build statistical models to understand phenomena, make predictions, and assess uncertainty in fields like pharmaceuticals, public health, or market research.
AI Research Scientist: While the program is "Applied AI," its strong theoretical foundations in machine learning and deep learning can lead to roles focused on fundamental research in artificial intelligence, exploring new AI theories and paradigms.
Data Product Manager: This role combines technical understanding with business acumen. Graduates define and oversee the development of data-driven products, ensuring they meet user needs and deliver business value, bridging the gap between engineering, design, and business teams.
