M.S. in IT Administration & Security
The M.S. in IT Administration & Security at NJIT provides a comprehensive curriculu...
B.S. in Data Science - Statistics
Newark, New Jersey
INTAKE: Jan & Sept
Program Overview
The Bachelor of Science in Data Science - Statistics at NJIT is designed to provide students with a comprehensive education in statistical methodologies and data science techniques. This program focuses on equipping students with the skills necessary to analyze and interpret complex data sets, apply statistical models, and use advanced analytical tools. The curriculum combines theoretical knowledge with practical applications, preparing graduates for various roles in data analysis and statistical research.
STEM-Designated: The B.S. in Data Science - Statistics is classified as a STEM (Science, Technology, Engineering, and Mathematics) program. This designation reflects the program’s emphasis on quantitative skills, technical expertise, and scientific principles. As a STEM program, it qualifies international students for an extended Optional Practical Training (OPT) period, allowing them to gain additional work experience in the U.S. after graduation.
ABET-Accredited: While the B.S. in Data Science - Statistics is not directly ABET-accredited, NJIT is renowned for its commitment to academic excellence and adherence to high standards across its programs. The university’s various ABET-accredited programs reflect its dedication to maintaining rigorous educational quality, ensuring that the B.S. in Data Science - Statistics upholds similar high standards in its curriculum and outcomes.
Curriculum: The curriculum for the B.S. in Data Science - Statistics provides a robust foundation in statistical theory and data analysis. Core courses include probability and statistics, data mining, statistical programming, and data visualization. Students also take advanced courses in statistical modeling, Bayesian statistics, and machine learning. The program emphasizes hands-on experience through projects and practical applications, preparing students for real-world data challenges.
Research Focus: NJIT’s B.S. in Data Science - Statistics program encourages students to engage in research activities that explore new methodologies and applications of statistics. Faculty members are involved in cutting-edge research in areas such as statistical learning, bioinformatics, and econometrics. Students may have opportunities to participate in research projects, contributing to advancements in statistical science and data analytics.
Industry Engagement: The program emphasizes strong connections with industry through internships, co-op programs, and industry-sponsored projects. NJIT collaborates with leading organizations to provide students with practical experience and exposure to real-world data challenges. Industry partnerships help students build professional networks, gain valuable insights into the field, and enhance their career prospects upon graduation.
Global Perspective: The B.S. in Data Science - Statistics program incorporates a global perspective by addressing international data challenges and trends. The curriculum includes global case studies, and students are encouraged to engage in research and projects with an international scope. This global outlook ensures that graduates are prepared to work in a diverse and interconnected world, understanding data issues from a worldwide perspective.
Location
Newark, New Jersey
Score
IELTS 6
Tuition Fee
USD 35934
Undergraduate Entry Requirements
Academic Qualifications: Applicants for undergraduate programs typically require a minimum academic achievement of 65% or above in their previous academic qualifications.
English Language Proficiency:
- IELTS: Overall band score of 6.0 with a minimum of 6.0 in each component.
- TOEFL: Overall score of 79 or higher.
- DET (Duolingo English Test): Overall score of 100.
New Jersey Institute of Technology (NJIT) recognizes the importance of supporting international students in pursuing their academic goals. To attract and assist talented students from around the world, NJIT offers several scholarships and financial aid options specifically designed for international students.
Global Highlander Scholarship: The Global Highlander Scholarship is a merit-based scholarship offered to incoming international undergraduate students. It is awarded based on academic achievements, leadership qualities, and extracurricular involvement. The scholarship amount varies and is renewable for up to four years, provided the student maintains the required GPA.
International Presidential Scholarship: The International Presidential Scholarship is another prestigious merit-based award available to exceptional incoming international undergraduate students. Recipients of this scholarship receive a substantial amount of financial aid to support their education at NJIT.
International Transfer Scholarship: International students transferring to NJIT from other universities or colleges may be eligible for the International Transfer Scholarship. This merit-based award aims to recognize academic excellence and provide financial support to deserving transfer students.
Educational Opportunity Fund (EOF) Grant: The Educational Opportunity Fund Grant is available to New Jersey residents, including eligible international students. This grant provides financial assistance to students with demonstrated financial need.
Albert Dorman Honors College Scholarship: The Albert Dorman Honors College at NJIT offers scholarships to students accepted into the Honors College program. These scholarships recognize academic excellence and provide enhanced educational opportunities and support.
Private and External Scholarships: In addition to NJIT-specific scholarships, international students may be eligible to apply for private or external scholarships that are not directly offered by the university. These scholarships may be provided by government agencies, organizations, foundations, or other institutions.
Graduates of the B.S. in Data Science - Computing program at NJIT are equipped with a broad skill set in data science and computing, making them highly versatile in the job market.
Data Scientist: Data scientists are experts in analyzing and interpreting complex data to provide actionable insights. They use statistical methods, machine learning algorithms, and data visualization tools to support decision-making processes. Data scientists are in high demand across various industries, including technology, finance, healthcare, and e-commerce.
Data Analyst: Data analysts focus on examining data to identify trends, patterns, and insights. They utilize tools such as SQL, Excel, and data visualization software to generate reports and dashboards. Data analysts often work in roles that support business operations, marketing strategies, and strategic planning.
Machine Learning Engineer: Machine learning engineers specialize in designing and implementing algorithms that enable computers to learn from data and make predictions. They develop and optimize machine learning models and systems to handle large-scale data. This role requires strong programming skills and a deep understanding of machine learning techniques and technologies.
Software Developer (with a Data Focus): Software developers with a focus on data design and build applications that process, analyze, and visualize data. They work on creating software solutions that handle big data and integrate data analytics into user-friendly applications. This role combines software engineering expertise with data science knowledge.
Business Intelligence (BI) Developer: BI developers create and manage systems that support data-driven business decisions. They design and develop BI solutions, including dashboards, reports, and data warehouses, to provide insights into business performance. BI developers work closely with data engineers and analysts to ensure the accuracy and relevance of the information.
Data Engineer: Data engineers are responsible for designing, constructing, and maintaining the infrastructure that supports data collection, storage, and processing. They build data pipelines and ensure that data systems are scalable, efficient, and reliable. Data engineers play a critical role in preparing data for analysis and ensuring data quality.
Quantitative Analyst: Quantitative analysts, often referred to as "quants," apply mathematical and statistical models to financial data to support investment and trading strategies. They work in finance, investment banking, and hedge funds, using their expertise to assess risk and identify profitable opportunities.
Data Consultant: Data consultants provide expert advice on data strategy, management, and analytics. They work with organizations to improve their data practices, implement new technologies, and optimize data usage. Data consultants often work on a project basis, offering tailored solutions to address specific business challenges.
Statistical Analyst: Statistical analysts use statistical techniques to analyze data and draw conclusions. They work in various sectors, including public health, economics, and social sciences, to support research and decision-making. Proficiency in statistical software and methodologies is essential for this role.
Research Scientist (Data Science): Research scientists in data science focus on advancing the field through innovative research and development. They explore new methodologies, algorithms, and technologies related to data science and computing. This role often involves working in academic or industrial research settings.
