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Applied to 415 Quant Jobs, Learn From My Mistakes

My Quantitative2023-06-19
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68K views|1 years ago
💫 Short Summary

The video provides a comprehensive overview of the speaker's background, including their journey as an international student in the UK, their master's degree in Engineering, and their application process for quantitative finance roles. The speaker shares their insights, predictions, and strategies for success, highlighting the importance of preparation, research, and perseverance in the competitive industry of quantitative finance.

✨ Highlights
📊 Transcript
The speaker discusses their background and the statistics collected from their application process for quantitative finance roles.
00:03
The speaker is an international student in the UK with a master's degree in Engineering.
They have one year of work experience at a startup in finance and technology.
The speaker also held a leadership position in their university's Finance society and their master's thesis was about machine learning in the engineering simulation environment.
The interview topics for quantitative finance roles can be divided into three broad categories: mathematics, data/machine learning, and quantitative trading.
05:22
Mathematics includes probability, statistics, and financial mathematics.
Data and machine learning cover handling and cleaning data, basic data engineering, and machine learning concepts.
Quantitative trading involves understanding the importance of backtesting and the metrics used in backtests.
The programming section includes classic data structures and algorithms, as well as specific language and design principle questions.
The speaker had a positive experience with interviews where they discussed their background, work experience, and skills, and received good feedback.
10:43
Researched in depth about the firm, the team, and the interviewers before each interview.
Rehearsed a good story about the transition to quant finance.
Made notes and refined interview skills.
Attacked their own CV to identify areas of focus.
The speaker discusses their predictions for the next hiring season, emphasizing the importance of being well-prepared for longer and more in-depth interviews, particularly in the areas of mathematics, programming, and machine learning.
13:05
Predicts longer and more in-depth interviews.
Emphasizes the importance of being well-prepared for mathematics, programming, and machine learning.
Mentions the increasing prevalence of data tests in the application process.
Advises to start preparation early and focus on storytelling skills.
💫 FAQs about This YouTube Video

1. What is the general application process for quantitative finance roles?

The general application process for quantitative finance roles involves CV screening, technical and non-technical assessments, and multiple interview rounds. It includes testing in mathematics, data handling, machine learning, and quantitative trading, with a focus on financial mathematics and programming. Candidates can expect an average of 5-6 rounds and should be prepared for a comprehensive evaluation of their skills and knowledge.

2. What are the key factors to consider when applying for quantitative finance roles?

When applying for quantitative finance roles, it is important to have a strong background in mathematics, finance, and programming. Candidates should focus on their quantitative and analytical skills, demonstrate expertise in data handling and machine learning, and showcase their ability to think critically and solve complex problems. Researching the firms and teams thoroughly, preparing for interviews across various technical topics, and having a well-structured and impressive CV are also crucial factors for a successful application.

3. How can candidates enhance their application for quantitative finance roles?

Candidates can enhance their application for quantitative finance roles by further developing their skills in mathematics, finance, and programming. Pursuing advanced studies, obtaining relevant certifications, and gaining practical experience in quantitative analysis and financial modeling can significantly strengthen their credentials. Additionally, actively engaging in research, staying updated on industry trends, and networking within the finance community can further distinguish their application.

4. What are the expectations for the next hiring season in quantitative finance?

The expectations for the next hiring season in quantitative finance include longer and more in-depth interviews, with a focus on mathematics, programming, and machine learning. Candidates should be prepared for an increasingly competitive and complex application process, where the ability to demonstrate expertise in quantitative analysis, financial mathematics, and advanced data handling techniques will be critical. The prevalence of machine learning in the industry suggests a greater emphasis on related skills during the hiring process.