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QS Rank:

verified

8

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University College London

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London

United Kingdom

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Program Rank

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9

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Total Tuition Fees

$47,100

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Duration

12 Months

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Median Salary

$1,10,000

Ranking

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#16

US World and News Report

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#18

The World University Rankings

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#8

QS World University Rankings

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Intake

Fall ( Sept - Nov )

Class Profile

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Class Size

25

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Average Age

26

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Average Work Experience

2 Years

Diversity

North America:

5%

Africa:

2%

Others:

6%

UK:

60%

Asia:

10%

South America:

2%

EU:

15%

Career Outcomes

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Median Earnings After Graduation

$1,10,000 / year

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Graduation Rate

95%

Prospective Job Roles

Data Quality Analyst

China Finance Analyst

Kinesiology Finance Manager

Healthcare Finance Manager

Finance

Manager of Finance

Green Finance Specialist

Director of Finance

Journalist

Librarian

Data scientist

Finance Manager

Top recruiters

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Eligibility Criteria

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At least 3 / 4 undergraduate GPA is expected.

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At least 15 years of bachelor degree.

English Proficiency Tests

  • IELTS

    6.5

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  • TOEFL

    92

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  • PTE

    75

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Standardised Test Score

  • GRE

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Application Requirements

Here's everything you need to know to ensure a complete and competitive application—covering the key documents and criteria for a successful submission.

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Application Fee: 90

  • intake

    Transcript

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    Passport

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    Statement of Purpose

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    Resume

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    IELTS

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    Academic LOR

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    Class 10 Marksheets

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    Class 12 Marksheets

Application Deadlines

Standard Deadline
FallJun 27, 2025

Fees and Funding

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Tuition Fees

$47,100 / year

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Overall Cost

$62,000 / year

FAQs

  • The UCL MSc Finance program is highly regarded for its academic excellence and strong career prospects.

  • Data science is becoming increasingly more important in the finance industry, as companies seek graduates whose main expertise is in finance but who also have a high level of data science literacy and skills.

  • Financial data science combines the traditions of econometrics with the technological components of data science. Financial data science uses machine learning, and predictive and prescriptive analytics to provide robust possibilities for understanding financial data and solving related problems.

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