LSE is best known for Economics, Law, and Politics, but its Department of Statistics has built one of the newer, more technical additions to LSE's course list in BSc Data Science and MSc Data Science, sitting alongside LSE's long-established quantitative programs (Actuarial Science, Statistics, Financial Mathematics). For applicants weighing a data science degree at a specialist social-science institution against a computer-science-focused university like Imperial or UCL, LSE's pitch is different: a data science education built on a foundation of economics, social statistics, and policy-relevant applications, inside a university whose overall global ranking undersells how strong it is in the quantitative social sciences specifically, and a central London location a short walk from the City's data and fintech employers.
This guide walks through what it takes to get into LSE's Data Science programs at both levels: acceptance rate realities, cost, requirements, English-test rules, and career outcomes.
Acceptance Rate: What LSE Actually Publishes
LSE does not publish a course-specific acceptance rate for Data Science at either level. Here is what is actually known, and how to read it honestly:
- LSE undergraduate (university-wide): LSE's widely reported 2025-cycle figures show roughly 1,900 places filled from around 30,000 UCAS applications, an overall acceptance rate close to 6%, against an offer rate (offers made, as distinct from places filled) closer to 16%. This is a blended, all-courses figure; LSE does not publish anything specific to BSc Data Science.
- MSc Data Science (graduate): LSE does not publish an aggregate postgraduate acceptance rate at all, for Data Science or any other course. LSE's general graduate standard applies: most taught master's courses expect at least an upper-second-class (2:1) honours degree or its recognised international equivalent, with quantitative background (mathematics, statistics, computer science, or a closely related field) the practical prerequisite for Data Science specifically, even though LSE does not publish a formal minimum-subject requirement in the data available.
Bottom line: treat the 6% university-wide undergraduate figure as an honest, if imprecise, proxy for BSc Data Science, since LSE gives no course-specific number at either level, and no acceptance-rate figure exists for the graduate course at all.
Fees and Cost of Attendance
LSE does not break out a Data Science-specific fee separately in the published data used here; the following uses LSE's representative modal fee tier (the fee band covering the most common Social Sciences and Statistics-adjacent courses on LSE's list), converted from GBP at roughly 1 GBP = 1.34 USD:
| Cost Item | BSc Data Science (Overseas/International, USD/year) | MSc Data Science (Overseas/International, USD/year) |
|---|---|---|
| Tuition | $41,138 (representative Overseas tier; always confirm the exact Statistics department fee on LSE's current course page) | $40,736 (representative Overseas tier; always confirm the exact fee on LSE's current MSc Data Science page) |
| Living expenses (central London) | $18,693 | $24,924 |
| Total estimated cost of attendance | ~$59,831 | ~$65,660 |
The Home (UK-domiciled) fee is fixed government-wide at GBP 9,790/year ($13,119) for undergraduates; LSE's Home graduate fee for the representative tier used here is roughly GBP 18,300/year ($24,522). Living costs are estimated from LSE's own official monthly budget guidance of GBP 1,550, applied over 9 months for undergraduates and 12 months for graduate students. Important caveat: because LSE prices individual courses on a per-course basis and does not publish one consolidated Data Science-specific figure in the data used for this guide, treat the numbers above as a reasonable representative estimate, not a precise Data Science quote, and check the specific course page before budgeting.
Admission Requirements
BSc Data Science (undergraduate, Department of Statistics):
- UCAS application and personal statement
- Academic reference from school/college
- Predicted or achieved A-Level, IB, or equivalent qualification grades; LSE's general undergraduate offer range runs from A*AA up to A*A*A depending on course, and a strong Mathematics result is the practical baseline expectation for a Statistics department course, even though LSE does not publish one universal fixed grade requirement for Data Science specifically
- English language proficiency test scores for applicants who do not qualify for a waiver
- No interview for the large majority of applicants; decisions are made holistically from the UCAS form, grades, and personal statement
MSc Data Science (graduate):
- Statement of purpose
- Two academic and/or professional references
- Official transcripts from all previously attended institutions
- CV/resume
- At least an upper-second-class (2:1) honours degree or its recognised international equivalent, generally in a quantitative subject (mathematics, statistics, computer science, economics, or a related field)
- English language proficiency test scores (if applicable)
- GRE/GMAT are not required for the large majority of LSE's graduate courses, and nothing in LSE's published policy suggests MSc Data Science is an exception
How to Get Into LSE's Data Science Program
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Lead with quantitative depth, not general coding ability. Because the program sits inside LSE's Department of Statistics rather than a computer-science department, admissions readers weigh mathematical and statistical grounding (calculus, linear algebra, probability, statistical inference) more heavily than programming experience alone, so a strong Mathematics grade profile matters more here than at a typical CS-department data science course.
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Use the personal statement to connect data science to a real-world, ideally social-science-adjacent, application. LSE's identity as a specialist social-science institution means admissions readers respond well to applicants who frame data science around economics, public policy, social measurement, or similar domains, rather than a purely technical pitch that could apply to any university.
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For the MSc, highlight prior coursework in statistics or econometrics specifically. Applicants coming from an undergraduate economics, mathematics, or engineering background should foreground any statistics, machine learning, or data analysis modules explicitly, since this signals fit with a Statistics-department program more directly than general software engineering experience.
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Clear the Writing component of IELTS/TOEFL with real margin. LSE's prep notes flag that quantitative-course applicants (Data Science, Statistics, Financial Mathematics included) often clear Reading and Listening comfortably but underprepare Writing, which matters for the dissertation and research-proposal components common across LSE graduate study.
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Apply within LSE's standard UCAS or rolling graduate timeline, not late. LSE follows the standard UK-wide UCAS mid-January deadline for undergraduates (notably later than Oxford and Cambridge's mid-October deadline) and a rolling, course-specific graduate cycle; there is no separate, earlier internal deadline specific to Data Science, but applying well ahead of any course's advertised deadline is still the safer path.
English Proficiency Requirement (IELTS/TOEFL)
LSE applies its standard unified undergraduate threshold and its graduate Standard tier to Data Science, since it is not among the small set of writing-intensive courses LSE places in its higher graduate tier:
- Undergraduate (BSc Data Science): IELTS Academic 7.0 overall with 7.0 in every component, or TOEFL iBT 100 overall with component minimums of Writing 27, Reading 25, Listening 24, and Speaking 24.
- Graduate, Standard tier (MSc Data Science): IELTS 7.0 overall with no element below 6.5, or an approximate TOEFL iBT equivalent around 100 overall.
- Waiver: applicants who are nationals of Canada or a UKVI-recognised majority English-speaking country with English as a first language are generally exempt, as are those who have completed a qualifying degree taught and examined entirely in English in one of those countries.
For the complete breakdown across all of LSE's courses, see LSE IELTS requirements and LSE TOEFL requirements.
Career Outcomes
LSE does not publish outcomes data broken out specifically for Data Science graduates at either level. The university-wide recruiter lists skew toward finance, consulting, and policy employers, several of which run dedicated data and analytics teams that actively recruit LSE's quantitative graduates:
- Top recruiters (undergraduate, university-wide): Goldman Sachs, McKinsey & Company, Deloitte, PwC, UK Civil Service, Bank of England
- Top recruiters (graduate, university-wide): McKinsey & Company, Goldman Sachs, Boston Consulting Group, Bain & Company, JPMorgan Chase, International Monetary Fund / World Bank
- LSE does not publish employment-rate or average starting-salary figures for either level in the data used here
None of these figures are Data Science-specific, but London's dense fintech and analytics job market, combined with LSE's central-London location and strong ties into the City's finance and consulting employers, gives Data Science graduates a practical pipeline into data and quantitative analyst roles at the same firms that recruit heavily from LSE's other quantitative courses.
FAQ
Does LSE publish a separate acceptance rate for Data Science? No. LSE's only published acceptance-rate figure is university-wide (roughly 6% for the 2025 undergraduate cycle), and it publishes no acceptance rate at all for any graduate course, Data Science included. Use the 6% figure only as an honest, imprecise university-wide proxy for the undergraduate course.
Is BSc Data Science run by LSE's computer science department? No. LSE does not have a separate computer science department; BSc and MSc Data Science sit within LSE's Department of Statistics, which shapes the program toward statistical and quantitative-methods training rather than a general software-engineering curriculum.
What IELTS or TOEFL score do I need for LSE Data Science? BSc Data Science applicants need IELTS 7.0 overall with 7.0 in every component (or TOEFL 100 with specific component minimums), the same unified standard LSE applies to all undergraduate courses. MSc Data Science falls under LSE's graduate Standard tier: IELTS 7.0 overall with no element below 6.5.
How much does LSE's BSc or MSc Data Science cost? LSE does not publish one Data Science-specific fee in the data used here; using LSE's representative fee tier, BSc Data Science runs roughly $41,138/year in tuition for international students (total cost of attendance around $59,831/year), and MSc Data Science runs roughly $40,736/year (total cost of attendance around $65,660/year). Always confirm the exact figure on LSE's current course page.
Is the GRE or GMAT required for MSc Data Science? LSE does not require a GRE or GMAT score for the large majority of its graduate courses, and nothing in LSE's published admissions policy suggests MSc Data Science is an exception, though applicants should confirm current policy on the specific course page.
Do I need a computer science background to apply to LSE Data Science? Not necessarily. Because the program is housed in the Department of Statistics, a strong mathematics or statistics background (at A-Level/IB for undergraduates, or in a prior degree for MSc applicants) is generally weighted at least as heavily as programming experience.