M.Sc. Applied Statistics and Data Analytics - Kristu Jayanti University

Department of Physical Sciences / M.Sc. Applied Statistics and Data Analytics

About the Programme

The M.Sc. Applied Statistics and Data Analytics programme is an advanced, industry-aligned postgraduate degree designed to build strong analytical, statistical, and computational competencies. As organizations increasingly depend on data-driven decision-making, the demand for professionals skilled in statistical modelling, machine learning, big data analytics, and computational tools continues to grow across healthcare, finance, business, public policy, technology, and research.

Applied Statistics provides the foundation for scientific data analysis through probability theory, estimation, hypothesis testing, regression modelling, multivariate techniques, sampling, and statistical quality control. Data Analytics focuses on transforming raw data into actionable intelligence using computational, algorithmic, and visualization techniques. Students gain hands-on exposure to modern analytical ecosystems including Python, R, SQL, machine learning frameworks, visualization tools, and big data platforms. The curriculum blends rigorous statistical theory with real-world applications, case studies, industry projects, internships, and software-driven learning.

Statistics + Analytics

Theoretical depth in applied statistics combined with practical proficiency in data analytics and computational tools.

Industry Tools

Hands-on exposure to Python, R, SQL, machine learning frameworks, visualization tools and big data platforms.

Data-Driven Careers

Prepares graduates for data-intensive roles in corporate, government, research institutions and academia.

M.Sc. Applied Statistics and Data Analytics students
ACADEMIC PATHWAYS

Future Carriers

Graduates pursue pathways in data science, analytics, research, government statistical systems, consulting and academia.

Career Roles

Data Scientist / Data Analyst
Statistical Analyst / Modeller
Business / Marketing Analyst
Machine Learning Associate
BI / Visualization Specialist
Research Analyst
Consulting Analyst
Government / Official Statistics Roles
Quality / SQC Analyst
Academic / Teaching Pathway

Employment Sectors

Data Science and Analytics Firms
Banking, Finance and Fintech
Healthcare and Public Health Analytics
Consulting and Professional Services
Technology and Product Companies
Government Statistical Systems
Market Research and FMCG
Public Policy and Research Institutes
Academia and Higher Studies
Corporate Analytics Teams
FOR A COMPLETE ACADEMIC PICTURE

Programme At a Glance

An industry-aligned postgraduate degree building analytical, statistical and computational competencies for data-driven careers.

Programme: Master of Science (M.Sc.)

Specialisation: Applied Statistics and Data Analytics

Duration: 2 Years (Postgraduate)

Mode: Full-Time Postgraduate Programme

Academic Focus: Statistical modelling, ML, big data analytics; R, Python, SQL, visualization and real-world applications

Pathway: Data science, analytics, research, government statistical systems, consulting and academia

Fee Structure Apply Now
CHECK IF YOU QUALIFY

Eligibility Criteria

Review the mandatory academic qualifications and minimum score criteria required for admission.

Candidates with a Bachelor’s degree preferably in Statistics, Mathematics, Computer Science or Economics with a minimum of 50% marks (45% for SC/ST candidates) are eligible, and a candidate who has studied Statistics as a minor/ancillary/subsidiary for at least 4 semesters is also eligible.

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CENTRE OF EXCELLENCE

Programme Outcomes

Outcome-based learning that unites statistical theory with modern analytics for data-intensive careers.

Advanced Statistical Methods

Estimation, inference, regression, ANOVA, multivariate analysis, time series, sampling theory, SQC and Bayesian methods.

Modern Analytics & ML

Machine learning basics, predictive modelling, supervised and unsupervised methods and statistical learning.

Computing & Programming

R programming, data wrangling, automation, and exposure to Python, SQL and analytical workflows.

Data Visualization & Reporting

Use of Excel, R Markdown, dashboards and visualization platforms (e.g. Power BI / Tableau).

Real-World Application

Applying statistical and analytical techniques to problems in business, healthcare, finance, marketing and public policy.

Research Skills

Literature review, proposal writing, data handling, experimental design and scientific documentation.

YOUR PATH TO SUCCESS

Why to Choose This Programme?

Organisations across healthcare, finance, business, public policy and technology rely on data-driven decisions. Professionals who combine statistical modelling with computational analytics are in high demand.

The M.Sc. Applied Statistics and Data Analytics at Kristu Jayanti builds strong analytical, statistical and computational competencies through rigorous theory, software-driven learning, case studies, projects and internships.

Choosing this programme enables students to:

  • Industry-integrated curriculum aligned with statistical modelling, analytics and AI-driven insights across sectors.
  • Advanced statistical expertise: probability, regression, multivariate analysis, sampling, SQC and applied modelling.
  • Hands-on analytical skills in R, Python, SQL, Power BI/Tableau and modern data analysis workflows.
  • Balanced theory–application approach through case studies, real datasets, research projects and internships.
  • High employability in data science, analytics, research, government statistical systems, consulting and academia.
  • Future-ready skill development in ML, predictive analytics, data mining, big data tools and industry best practices.

With dual strength in applied statistics and data analytics, graduates are prepared for data-intensive roles across corporate, government, research and academia.