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Position:

Quantitative Researcher Python Buy Side Hong Kong or Singapore Hong Kong

Job Category:

Information Technology

Target:

Management (Manager/Director of Staff)

Salary:

/ Yearly

Description:

Our client, a leading firm in the financial industry, is seeking a Quantitative Researcher with 5-7 years of experience to join their team in either Hong Kong or Singapore. The ideal candidate will have a background from the buy-side.

As a Quantitative Researcher, you'll be responsible for developing and implementing quantitative trading strategies. The role will focus on a low to mid-frequency trading style. The strategies will cover global markets, with a particular emphasis on the US and Pan-Asia regions. Experience with US/Europe arbitrage strategies is also highly valued.

You'll have the opportunity to work closely with the existing team and will eventually report to a new senior portfolio manager who will join the firm next year. This is an excellent opportunity to be part of a dynamic trading environment.

Key Qualifications:
- 5-7 years of experience in a quantitative research role, preferably on the buy-side.
- Proficiency in Python and other standard programming languages.
- Strong knowledge of global markets, including the US and Pan-Asia.
- Ability to communicate in Mandarin is advantageous for liaising with Mandarin-speaking clients, but not mandatory
- Experience with arbitrage strategies is a plus.

If this outstanding opportunity sounds like your next career move, please send your resume in Word format to Charlie Kim at resume[at]pinpointasia.com and put Quantitative Researcher (Python/Buy Side) [Hong Kong or Singapore] in the subject header. Data provided is for recruitment purposes only.

Pinpoint Asia is the leading specialist Financial IT recruitment firm in the Asia Pacific region. Visit Pinpoint Asia’s website at pinpointasia.com today to see other exciting job opportunities.

Job Available in:

Hong Kong

Employer`s Country:

Hong Kong SAR, PRC

Job Viewed:

1 times.

This job offer will expire in 25 day(s).


 

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