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05 Sep 2025, 06:39
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Male/UK/24
Top 25 Russel Group University UK - BA Business Economics - Grade achieved: 1st (4.0 GPA) - Modules inc: calculus, statistics, finance, econometrics, game theory
Gmat - 655 Q82, V84, DI82
Relevant Work exp - 1.5 yrs as a data analyst at a strategy consultancy startup and a FTSE 250 financial services company. Mainly use Excel, VBA and Power BI
Other qualifications - Microsoft MS-300 Power BI certified, Spanish speaker, competitive basketball, recreational poker
Looking to develop my quantitative skills and apply to MSc Finance and MSc Financial Statistics at LSE and Imperial this year to get into IB. Is my GMAT quant score too low for these programs? I think I could score slightly higher, but at the cost of delaying my application, perhaps even to R2. TIA
Top 25 Russel Group University UK - BA Business Economics - Grade achieved: 1st (4.0 GPA) - Modules inc: calculus, statistics, finance, econometrics, game theory
Gmat - 655 Q82, V84, DI82
Relevant Work exp - 1.5 yrs as a data analyst at a strategy consultancy startup and a FTSE 250 financial services company. Mainly use Excel, VBA and Power BI
Other qualifications - Microsoft MS-300 Power BI certified, Spanish speaker, competitive basketball, recreational poker
Looking to develop my quantitative skills and apply to MSc Finance and MSc Financial Statistics at LSE and Imperial this year to get into IB. Is my GMAT quant score too low for these programs? I think I could score slightly higher, but at the cost of delaying my application, perhaps even to R2. TIA
06 Sep 2025, 00:27
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- Profile strength: First-class BA from a Russell Group uni with strong quant modules; solid early-career data-analytics experience; useful extras (Power BI cert, Spanish, competitive sport). Overall competitive for top UK MScs.
- GMAT verdict (655; Q82): Good, but not differentiating for LSE/Imperial’s most quant-heavy tracks. Admitted cohorts often skew to Q more than 90th percentile. Your Q82 won’t auto-ding you, but pushing it up materially helps.
- In terms of the programs:
a) LSE MSc Finance (pre-experience): Ultra-competitive; a higher Q (and/or higher total) would noticeably improve odds.
b) LSE MSc Financial Statistics: Very quant-leaning; your transcript helps, but they expect clear, recent proof of advanced math comfort-higher Q or GRE-Q strengthens.
c) Imperial MSc Finance: Competitive with your academics; higher Q boosts both admit and scholarship chances.
d) Imperial MSc Financial Statistics: Similar to LSE FinStats. Emphasize rigorous math/econometrics and recent quantitative work.
- GMAT verdict (655; Q82): Good, but not differentiating for LSE/Imperial’s most quant-heavy tracks. Admitted cohorts often skew to Q more than 90th percentile. Your Q82 won’t auto-ding you, but pushing it up materially helps.
- In terms of the programs:
a) LSE MSc Finance (pre-experience): Ultra-competitive; a higher Q (and/or higher total) would noticeably improve odds.
b) LSE MSc Financial Statistics: Very quant-leaning; your transcript helps, but they expect clear, recent proof of advanced math comfort-higher Q or GRE-Q strengthens.
c) Imperial MSc Finance: Competitive with your academics; higher Q boosts both admit and scholarship chances.
d) Imperial MSc Financial Statistics: Similar to LSE FinStats. Emphasize rigorous math/econometrics and recent quantitative work.
