RBI Grade B DSIM 2027: Exam Dates, Eligibility, Exam Pattern, Full Syllabus and Strategy for Statistics and Data Science Graduates
RBI Grade B DSIM 2027 recruits statisticians and data scientists. The tentative calendar has the notification in February 2027, Paper-I in April 2027 and Papers II and III in May/June 2027. Eligible degrees (as in 2026): a Master's (55%) in Statistics, Maths, Econometrics, Informatics, Data Science, AI, ML or Big Data, or a 4-year Bachelor's (60%) in these fields. There are 3 papers (300 marks) plus a 75-mark interview, covering PG-level probability, inference, econometrics, ML, deep learning and SQL. PY 2026 had 10 DSIM posts.
RBI Grade B 2027 tentative schedule (RBI recruitment calendar, as on 22.10.2026, for Officers in Grade 'B' (DR) General/DEPR/DSIM)
| Stage | Month |
|---|---|
| Notification (online application opens) | February 2027 |
| Phase-I examination | April 2027 |
| Phase-II examination | May / June 2027 |
| Interview and final result | After Phase-II results (dates to be announced) |
These are month-level tentative dates. Exact dates for each cadre and paper will be in the February 2027 notification and the admit cards. In 2026, DSIM Paper-I was held with DEPR Phase-I, and Papers II and III with DEPR Phase-II.
RBI Grade B DSIM 2027: Overview
| Particular | Details |
|---|---|
| Post | Officer in Grade 'B' (DR) DSIM (Department of Statistics and Information Management), Panel Year 2027 |
| Notification | February 2027 (tentative) |
| Paper-I | April 2027: Objective Statistics, 100 marks, 120 min |
| Paper-II and III | May / June 2027: Descriptive Statistics (180 min) + English (90 min) |
| Total marks | 300 written + 75 interview = 375 |
| Final merit | Paper-I + II + III + Interview |
| Vacancies | To be announced (PY 2026: 10) |
| Qualification | Master's (55%) in Statistics, Maths, Econometrics, Data Science, AI, ML etc., or a 4-year Bachelor's (60%) |
| Age limit (expected) | 21 to 30 years as on 01 April 2027 (+2/+4 for M.Phil/Ph.D) |
| Starting basic pay (PY 2026) | ₹78,450 (gross about ₹1,54,936 per month without HRA) |
RBI Grade B DSIM 2027 Exam Date vs 2026
| Stage | 2026 (actual) | 2027 (tentative) |
|---|---|---|
| Notification | 29 April 2026 | February 2027 |
| Phase-I | 14 June 2026 (Paper-I) | April 2027 |
| Phase-II | 26 July 2026 (Papers II and III) | May / June 2027 |
| Gap: notification to Phase-I | About 6 weeks | About 2 months |
The DSIM syllabus is a full PG statistics curriculum plus ML and SQL. With Paper-I in April 2027, finish your first full pass by January and spend February and March on mocks and handwritten Paper-II practice.
RBI DSIM Job Profile: A Data Scientist at the Central Bank
The latest notification describes a heavily data-science-oriented DSIM role. Officers:
- Collect, compile and analyse banking, corporate and external-sector data.
- Model and forecast inflation and growth using classical and Bayesian inference, high-dimensional regression, time-series and simulation methods.
- Design and run complex sample surveys, construct index numbers and measure inequality.
- Manage large structured and unstructured datasets, write and optimise database queries, and maintain RBI's centralised reporting systems and data warehouse.
- Apply data science, AI and machine learning to extract insights for policy and operations.
RBI Grade B DSIM Vacancy 2027
To be announced in February 2027. For reference, PY 2026:
| UR | EWS | OBC | SC | ST | Total | PwBD (horizontal) |
|---|---|---|---|---|---|---|
| 4 | 1 | 4 | 1 | 0 | 10 | A: 1 |
RBI Grade B DSIM 2027 Eligibility
Essential qualification (any one, PY 2026 rule)
| Option | Degree | Subjects | Minimum marks |
|---|---|---|---|
| (a) | Master's | Statistics, Mathematics, Mathematical Statistics, Applied Statistics, Quantitative Economics, Econometrics, Informatics or related branches | 55% |
| (b) | Master's | Data Science, Artificial Intelligence, Machine Learning, Big Data Analytics or related branches | 55% |
| (c) | 4-year Bachelor's | Statistics, Mathematical/Applied Statistics, Quantitative Economics, Econometrics, Informatics, Data Science, AI, ML, Big Data Analytics or related | 60% |
SC/ST/PwBD candidates need 50% under all three options. Degrees must be from an institution recognised by the Government/UGC/AICTE. Desirable: a doctorate in these subjects is given preference, and research, teaching and publications count as additional qualifications.
Age limit 2027 (expected)
Age limit: In the 2026 cycle candidates had to be 21 to 30 years old on 01 April 2026 (born 02 April 1996 to 01 April 2005). If RBI keeps the same rule for 2027, the cut-off date would be 01 April 2027, meaning born between 02 April 1997 and 01 April 2006. This is our projection; confirm it in the February 2027 notification.
| Category (PY 2026 rules) | Relaxation |
|---|---|
| SC / ST | 5 years |
| OBC (Non-Creamy Layer) | 3 years |
| PwBD (Gen/EWS / OBC / SC-ST) | 10 / 13 / 15 years |
| Ex-servicemen, ECOs/SSCOs (5 years' service) | 5 years |
| M.Phil / Ph.D in specified subjects | 2 / 4 years |
| Research/teaching experience at a recognised university | Years of experience, max 3 (probation not counted) |
In PY 2026 you could apply for DSIM or DEPR, not both, and could also apply for the General cadre separately.
RBI Grade B DSIM Exam Pattern 2027
| Paper | Type | Mode | Duration | Marks |
|---|---|---|---|---|
| Paper-I (Apr 2027) | Objective (Statistics) | Online MCQ | 120 min | 100 |
| Paper-II (May/Jun 2027) | Descriptive (Statistics) | Question on screen, answers written on paper; on-screen calculator | 180 min | 100 |
| Paper-III (May/Jun 2027) | English (Descriptive) | Typed on keyboard, English only | 90 min | 100 |
| Interview | Personal interview | Hindi or English | 75 | |
| Total | 375 |
- Shortlisting for Papers II and III is based on Paper-I marks against a cut-off linked to the number of vacancies.
- All three papers and the interview count in the final merit.
- Physical calculators are banned, but a non-programmable on-screen calculator is provided for Paper-II (DSIM only).
- Papers I and II are set at the standard of a post-graduate degree examination.
RBI Grade B DSIM Syllabus 2027 (Paper-I and Paper-II)
As per the official PY 2026 syllabus. Papers I and II share one 9-unit syllabus: Paper-I tests it through MCQs, Paper-II through derivations, proofs, numericals and applied questions.
| Unit | Official topics |
|---|---|
| 1. Probability, Distributions and Sampling | Classical and axiomatic probability, Bayes theorem, weak and strong laws of large numbers, characteristic functions, CLT, probability inequalities; Binomial, Poisson, Geometric, Negative Binomial, Uniform, Normal, Exponential, Logistic, Log-normal, Beta, Gamma, Weibull, Bivariate Normal; Chi-square, t, F, Z; large-sample tests and contingency tables; SRS, stratified, systematic, cluster, two-stage and PPS sampling; ratio and regression estimation; non-sampling errors and non-response |
| 2. Linear Models and Economic Statistics | Vector spaces, partitioned inverse, g-inverse, orthogonal and idempotent matrices, eigenvalues, Cayley-Hamilton, quadratic forms; simple and multiple regression, Gauss-Markov, WLS, Box-Cox, inverse regression, multicollinearity, ridge, LASSO, Elastic Net, model selection, residual diagnostics, dummy variables, outliers; index numbers (chain/fixed base, splicing, deflating); Gini coefficient, Lorenz curve; basics of macroeconomics and national accounts |
| 3. Statistical Inference | Unbiasedness, sufficiency, consistency, efficiency; factorisation theorem; completeness; MVUE; Rao-Blackwell, Lehmann-Scheffe; Cramer-Rao; method of moments, MLE, least squares, minimum chi-square, Bayes estimators; Type I/II errors, p-value, power, Neyman-Pearson, UMP, likelihood ratio tests, goodness of fit, Bartlett's test; Kolmogorov-Smirnov, sign, Wilcoxon, Mann-Whitney, Kruskal-Wallis, Friedman, Kendall's tau, Spearman; order statistics, kernel density estimation |
| 4. Stochastic Processes | Poisson process (arrival and inter-arrival distributions, non-homogeneous, compound); Markov chains (TPM, Chapman-Kolmogorov, stationary distributions, periodicity, limit theorems); Brownian motion; martingales |
| 5. Multivariate Analysis | Multivariate normal; logit and probit; Mahalanobis D²; LDA; canonical correlation; PCA; factor analysis; cluster analysis |
| 6. Econometrics and Time Series | GLM, OLS, GLS, heteroscedasticity, autocorrelation tests, Theil BLUS, multicollinearity; IV, panel and distributed-lag models; simultaneous equations, identification (rank and order conditions); stationarity, AR, MA, ARMA, ACF/PACF, Box-Jenkins, ARCH/GARCH; ARIMA/SARIMA, order of integration, unit-root tests |
| 7. Optimization and Statistical Computing | Taylor's theorem, convex and coercive functions; Newton, gradient, conjugate-gradient and quasi-Newton methods; penalty methods, Lagrange multipliers; LPP, simplex; simulation, jack-knife, bootstrap, cross-validation; robust, nonlinear and generalised linear regression; tree-based methods; EM algorithm, imputation; Bayesian modelling, MCMC, Gibbs sampling, Metropolis-Hastings, annealing; neural networks, association rules |
| 8. Data Science, AI and ML | Supervised, unsupervised and reinforcement learning; accuracy measures; linear, logistic and penalised regression; Naive Bayes, k-NN, decision trees, SVM, kernel methods; random forests; k-means, k-medoids, linkage clustering, Dunn index, gap statistic; bagging and boosting (AdaBoost, gradient boosting); RNN, CNN, NLP; RFE, VIF, stacking, Elastic Net, grid-search tuning, feature importance, cross-validation strategies |
| 9. Database and Data Warehouse Management | Data structures; RDBMS and NoSQL fundamentals; normalisation; SQL querying, updating and aggregation; inner, left, right and outer joins; document, key-value, wide-column and graph databases; star and snowflake schemas; ETL; OLAP vs OLTP; indexing and optimisation; big-data frameworks |
Paper-III (English): tests writing skills, expression and understanding of the topic.
RBI Grade B DSIM 2027: statistics, ML and SQL preparation
PG-level statistics, machine learning and data science notes and mock tests from Piyush Wairale (IIT Madras), mentor to a GATE DA All India Rank 2. Includes the AI, ML & Data Science course built for bank officer exams.
View DSIM-ready CoursesWhere to Focus: Unit Priority for DSIM
| Priority | Units | Why |
|---|---|---|
| Very high | Inference (3), Linear Models (2), Probability and Sampling (1) | The core of every PG statistics exam; feeds both MCQs and long derivations |
| High | Econometrics and Time Series (6), ML (8) | Directly match the forecasting and analytics job role |
| Medium | Multivariate (5), Optimisation and Computing (7), Databases and SQL (9) | Shorter and concept-heavy; SQL joins and normalisation are quick marks |
| Focused | Stochastic Processes (4) | A narrow list: Poisson, Markov chains, Brownian motion, martingales |
This priority is our guidance based on syllabus depth and the job description; RBI does not publish unit-wise weightage.
Recommended Books for RBI DSIM
| Unit | Standard texts |
|---|---|
| Probability and Inference | Rohatgi & Saleh; Casella & Berger Statistical Inference; Gupta & Kapoor |
| Sampling | Cochran Sampling Techniques; Mukhopadhyay |
| Linear Models and Regression | Montgomery, Peck & Vining; Searle |
| Multivariate | Johnson & Wichern Applied Multivariate Statistical Analysis |
| Econometrics and Time Series | Gujarati; Box, Jenkins & Reinsel; Hamilton |
| Stochastic Processes | Karlin & Taylor; Sheldon Ross |
| ML and Data Science | James et al. An Introduction to Statistical Learning; Hastie et al. Elements of Statistical Learning |
| Databases | Korth, Silberschatz & Sudarshan Database System Concepts |
DSIM 2027 Preparation Timeline
| Window | Focus |
|---|---|
| Nov 2026 | Units 1 and 3: probability, distributions, sampling, estimation and testing |
| Dec 2026 | Units 2, 5 and 6: linear models, multivariate analysis, econometrics and time series |
| Jan 2027 | Units 7, 8 and 9: optimisation, computing, ML/DL, SQL; plus Unit 4 |
| Feb 2027 | Apply; start daily handwritten Paper-II practice with an on-screen-style calculator |
| Mar 2027 | Paper-I mocks every other day; one English essay a week |
| Apr 2027 | Paper-I exam |
| May / June 2027 | 180-minute Paper-II mocks; derivation and formula revision; Paper-III essays |
- Theory before tools: Paper-II is handwritten and proof-heavy. Practise the Rao-Blackwell, Cramer-Rao, Neyman-Pearson and Gauss-Markov derivations end to end.
- Link ML to statistics: ridge, LASSO, Elastic Net, cross-validation and boosting appear in both Unit 2 and Unit 8, so learn them once, deeply.
- Write SQL on paper: joins, GROUP BY with HAVING and nested queries by hand; know star vs snowflake schemas and OLAP vs OLTP.
- Practise with a basic calculator: Paper-II runs 180 minutes, and numerical speed decides whether you finish.
- Write English weekly: Paper-III is a full 100 marks in the final merit.
Coming from GATE DA or a data science degree?
Your ML, probability and linear algebra overlap heavily with DSIM. Close the gap with focused statistics and econometrics practice before April 2027.
Explore Test Series & NotesRBI Grade B DSIM 2027: Frequently Asked Questions
When is the RBI Grade B DSIM 2027 exam?
Paper-I is tentatively in April 2027, and Papers II and III in May/June 2027. The notification is expected in February 2027, as per RBI's recruitment calendar (as on 22.10.2026).
How many vacancies are there in RBI Grade B DSIM 2027?
They will be announced in February 2027. PY 2026 had 10: UR 4, EWS 1, OBC 4 and SC 1, with one horizontal PwBD seat in category A.
Can B.Tech Data Science or AI graduates apply for RBI DSIM?
Under the 2026 rules, yes, with a 4-year Bachelor's in Data Science, AI, ML, Big Data Analytics or a related branch and at least 60% (50% for SC/ST/PwBD).
Can M.Tech or M.Sc Data Science graduates apply for RBI DSIM?
Yes. A Master's in Data Science, Artificial Intelligence, Machine Learning, Big Data Analytics or related branches with 55% was an essential qualification option in 2026.
What is the RBI Grade B DSIM exam pattern?
Paper-I: objective statistics, 100 marks, 120 minutes. Paper-II: descriptive statistics written on paper, 100 marks, 180 minutes. Paper-III: typed English descriptive, 100 marks, 90 minutes. Interview: 75 marks.
Is a calculator allowed in the RBI DSIM exam?
Physical calculators are not allowed. A non-programmable on-screen calculator is provided for DSIM Paper-II only.
Is SQL part of the RBI Grade B DSIM syllabus?
Yes. Unit 9 covers RDBMS, NoSQL, normalisation, SQL querying and aggregation, joins, data warehousing, star and snowflake schemas, ETL, OLAP vs OLTP and indexing.
Does the DSIM syllabus include deep learning?
Yes. Unit 8 lists neural networks, recurrent neural networks, convolutional neural networks and natural language processing alongside classical ML methods.
Other RBI Grade B 2027 Guides
RBI Grade B 2027: All Cadres
Dates, vacancies, eligibility, age, salary, fee and exam pattern compared across General, DEPR and DSIM.
RBI Grade B General 2027
Any-discipline graduates. Phase-I GA, English, Quant, Reasoning; Phase-II ESI, English, Finance & Management.
RBI Grade B DEPR 2027
MA/MSc Economics or Finance. Objective and descriptive economics plus English writing.