Quantitative Developer
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Before you apply
LocationShanghai
Work modeon-site
Typefull-time
SeniorityMid
Experience1–5 yrs
DepartmentEngineering
Company size51–200 people
PostedJan 23, 2025 · 1y ago
Verified live1d ago
May no longer be actively hiring
Posted by the company on Jan 23, 202593% of this company's open roles have been listed for 90+ days
At a glanceSummarised by Seekless from the posting.
Bachelor's degree or higher in computer science or a related technical area
1-5 years of experience in programming for a professional setting
Proficiency in the Python programming language and its scientific computing ecosystem (numpy, Pandas, Arrow, etc.)
Being fast, rigorous and critical in thinking
Effective communicator with a strong sense of teamwork
Highly motivated and capable of thriving in a fast-paced environment
Familiarity with the state-of-the-art data engineering ecosystem
Experience in processing financial data
Experience in machine learning
Knowledge of quantitative research and trading
Skills
Python
numpy
Pandas
Arrow
machine learning
Responsibilities
Job Responsibilities:
1.
Design, develop, maintain, and optimize in-house research data platforms (including price volume, fundamental, and alternative data), providing quantitative researchers with reliable, high-quality, and stable data sources and analysis tools.
2.
Establish protocols for data injection, processing, quality assurance, anomaly detection and archiving, and streamline and improve processes.
3.
Work with external partners to onboard new datasets, conduct domain-specific data analysis and data mining for new datasets, and collaborate with quant researchers to evaluate new data sources.
4.
Develop and maintain quantitative research tools.
Requirements
Qualifications:
1.
Bachelor’s degree or higher in computer science or a related technical area.
2.
1-5 years of experience in programming for a professional setting.
3.
Proficiency in the Python programming language and its scientific computing ecosystem (numpy, Pandas, Arrow, etc.) is preferred.
4.
Familiarity with the state-of-the-art data engineering ecosystem is a plus.
5.
Experience in processing financial data is a plus.
6.
Experience in machine learning is a plus.
7.
Knowledge of quantitative research and trading is a plus.
8.
Being fast, rigorous and critical in thinking.
9.
Effective communicator with a strong sense of teamwork.
10.
Highly motivated and capable of thriving in a fast-paced environment.