Statisticians collect, analyze, and interpret data to inform decision‑making across industries like healthcare, finance, government, tech, and social sciences. They design surveys and experiments, build predictive models, and communicate findings to stakeholders. The growing data‑driven world makes their work essential.
Ideal candidates are:
Analytical and comfortable with math.
Curious and detail‑oriented.
Good communicators able to explain technical results.
Interested in problem-solving across diverse fields like finance, public policy, health, etc.
In India: 10+2 with Mathematics or Statistics, usually ≥ 50 % marks
Abroad: Often requires 12th (or equivalent) with strong math grade; universities may ask for standardized tests (SAT/ACT) and English proficiency (IELTS/TOEFL).
India:
CUET‑UG/PG for central universities
IIT‑JAM for admission to IIT/MSc-type programs
ISI‑B.Stat entrance for Indian Statistical Institute
Global:
Required SAT/ACT, possibly AP/IB scores.
International programs may require a portfolio or quantitative test scores (GRE for MS programs).
Top institutions include:
Indian Statistical Institute (ISI), Kolkata – flagship B.Stat (3 yrs) & B.Stat DS (4 yrs) programs
University of Delhi (DU) – via CUET; prominent colleges like St. Xavier’s, MJ College
Christ University, Bangalore; Loyola & MCC Chennai; Ferguson Pune also rank highly for BSc Statistics
Harvard
Stanford
UC Berkeley
University of Toronto
London School of Economics.
Generally 3 years, semester system:
Foundation in calculus, probability, linear algebra, statistical inference.
Core topics: regression, sampling, design of experiments, time series, multivariate analysis.
Practical: lab work using R, Python, SPSS, Excel
Many programs include internships or research projects.
After a bachelor’s:
MSc/MA in Statistics, Data Science, Actuarial Science.
MTech in QROR/CS at ISI.
MBA for analytics roles.
Research: MPhil, PhD, or civil services via UPSC (Indian Statistical Service)
Mathematical & statistical theory.
Data handling and visualization.
Programming in R, Python, SQL.
Logical thinking, problem-solving, communication.
Statisticians
Data Analysts/Scientists
Risk/Market Analysts
Actuaries
Biostatisticians
Research Officers
R, Python, SQL
SPSS, SAS, Excel
Tableau, Power BI (for visualization)
Some exposure to MATLAB, Hadoop, TensorFlow