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moomoo2027 Fresh Grad Hire - Algorithm Engineer (Financial Securities Algorithm R&D Fo
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Before you apply
LocationShenzhen, Guangdong Province, China
Typefull-time
SeniorityEntry
Company size1,001–5,000 people
PostedOct 22, 2026 · 2w ago
Verified live15h ago
At a glanceSummarised by Seekless from the posting.
Bachelor's degree or above in Financial Engineering, Computer Science, Applied Mathematics, or a related STEM field
Familiarity with securities trading mechanisms and a basic understanding of algorithmic execution or option pricing
Solid programming fundamentals; proficiency in at least one language such as Python or Go; ability to implement algorithms and models as runnable code
Respect for financial business, data, and rules; risk awareness and sensitivity to pricing, executions, and anomalous results; clear logical thinking and effective communication and collaboration
Good English & Chinese listening, speaking, reading, and writing skills; ability to read English technical literature fluently and to communicate in both day-to-day and technical contexts
Internship or project experience in quantitative finance, securities firms, exchanges, or fintech is preferred
Basic knowledge of machine learning is preferred
Project or research experience in machine learning, deep learning, or option pricing
Hands-on experience applying AI tools to model research or code implementation
Open to candidates graduating between January 2026 and August 2027
Skills
Python
Go
machine learning
deep learning
Responsibilities
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Participate in the design and development of systems including algorithmic orders, quantitative models, and smart order routing, translating algorithmic designs into runnable and verifiable system implementations.
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Participate in the research and optimization of execution algorithms such as TWAP and VWAP, as well as machine learning–based strategies, with a focus on execution performance and result reproducibility.
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Participate in the development and optimization of algorithms and systems related to option pricing and volatility surfaces, with attention to the correctness of pricing logic, parameters, and boundary conditions.
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Make appropriate use of AI tools to improve efficiency in research and development, and validate key outputs such as model results, executions, and pricing.
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Read English technical literature, interface protocols, and relevant market materials, and engage in day-to-day and technical communication with business and engineering teams.
Requirements
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Education: Bachelor’s degree or above in Financial Engineering, Computer Science, Applied Mathematics, or a related STEM field.
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Financial knowledge: Familiarity with securities trading mechanisms and a basic understanding of algorithmic execution or option pricing; internship or project experience in quantitative finance, securities firms, exchanges, or fintech is preferred.
•
Technical skills: Solid programming fundamentals; proficiency in at least one language such as Python or Go; ability to implement algorithms and models as runnable code; Basic knowledge of machine learning is preferred.
•
Work attributes: Respect for financial business, data, and rules; risk awareness and sensitivity to pricing, executions, and anomalous results; clear logical thinking and effective communication and collaboration.
•
Language skills: Good English & Chinese listening, speaking, reading, and writing skills; ability to read English technical literature fluently and to communicate in both day-to-day and technical contexts.
•
Preferred qualifications: Project or research experience in machine learning, deep learning, or option pricing; hands-on experience applying AI tools to model research or code implementation.
*Open to candidates graduating between January 2026 and August 2027.