Department of Statistics

Overview

Established in 2019, the Department of Statistics offers M.Sc. Biostatistics (with internship opportunities), M.Sc. Data Science, and Doctoral Programs. The Department is committed to delivering high-quality education through a blend of classroom teaching and practical exposure. Lectures are conducted in ICT-enabled classrooms, while practical sessions use real-world datasets in a well-equipped laboratory setting. Innovative teaching methods such as journal club presentations based on multidisciplinary research articles, case studies, quizzes, and assignments focused on real-life problem statements.

The Department actively contributes to the University in several ways. In research, faculty members serve on scientific review boards and doctoral advisory committees, provide statistical consultancy which include sample size calculation, identification of sampling technique and study designs, data analysis, report preparation, manuscript writing, and provide assistance in answering publication queries.

In teaching, the Department offers value-added courses such as SQL, certificate courses in R, and statistical software training for undergraduate, postgraduate, and research scholars. Additionally, the Department promotes skill development by organizing workshops on statistical methods and research, with a strong focus on practical application and hands-on learning. The Department also provides industrial exposure by inviting professionals from reputed industries. Through these efforts, the Department of Statistics plays a pivotal role in enhancing the academic and research environment of the University.

M.Sc. Biostatistics

The M.Sc. Biostatistics program is a two-year postgraduate program designed to equip students with strong theoretical and practical skills in statistical methods applied to health and life sciences. It emphasizes real-world data analysis, programming proficiency, and research exposure, preparing students for careers in biomedical research, pharmaceuticals, public health, and academia. With training in software such as R, Python, SPSS, and G*Power, along with opportunities for internships and interdisciplinary collaboration, the program provides a solid foundation for both professional advancement and further research in biostatistics.

Why Us?

• Strong theoretical foundation in Biostatistics.
• Data-centric teaching approach.
• Regular exercises, assignments, and practicals based on real-world data
• Provision to work in multiple programming environments (SPSS, R, Python, EPI Info, G* Power)
• Statistical Consultation: Continuous interaction with researchers of various health domains.
• Internship opportunities.
• Access to enormous databases and research journals.
• Extensive job opportunities both in the private and public sectors.

Career Opportunities

• Statistical Programmer: Analyse clinical trial data and develop statistical code for pharma, CROs, and research units.
• Biostatistician: Calculate sample size, identify study design, handle biomedical data analysis, and support health research and drug development.
• Academia: Work as a Biostatistician or faculty in medical colleges and universities.
• Public Sector: Roles in government health departments, statistical divisions, and policy planning bodies.
• Research Institutions: Positions in organizations like ICMR, NIMHANS, and other health research centres.
• Freelancing/Consulting: Offer independent statistical support for research, healthcare startups, and industry projects.

M.Sc. Data Science

The M.Sc. Data Science program is a two-year postgraduate program designed to build expertise in data analysis, machine learning, and computational techniques. It combines strong theoretical foundations with practical training in handling large-scale data from diverse domains such as business, healthcare, finance, and technology. The program trains students to extract insights from data, solve real-world problems, and contribute to data-driven decision-making. With hands-on experience in tools like R, Python, SQL, and cloud-based platforms, students are well-prepared for careers in industry, academia, and research.

Why Us?

• In-depth training in statistical modeling, machine learning, and data visualization.
• Project-based learning using real-world datasets
• Exposure to multiple programming languages and environments (Python, R, SQL, Power BI, Excel)
• Collaboration with industries and academic departments for applied projects.
• Regular workshops and guest lectures from data science professionals.
• Access to cloud computing, big data platforms, and research databases.
• Strong placement support and career guidance.

Career Opportunities

• Data Scientist: Build predictive models, analyze trends, and drive decision-making using data.
• Data Analyst: Interpret complex datasets, generate actionable insights, and create dashboards.
• Machine Learning Engineer: Develop, test, and deploy machine learning algorithms in real-world applications.
• Business Intelligence Analyst: Help organizations make strategic decisions using data visualization and reporting tools.
• Academic and Research Roles: Opportunities in teaching and applied data science research.
• Industry and Consulting: Work with IT firms, startups, healthcare, and finance companies offering data-driven solutions.
• Entrepreneurship/Freelancing: Provide data analytics solutions independently or build your own data-focused ventures.

Contact Us

+91 9448546006, +91 9686140870

statistics@yenepoya.edu.in