FinTech Analyst

AVALOK CAPITAL LIMITED; Hong Kong; On-site; HKD 1,000,000 - 1,800,000; Full time

Job summary

AVALOK CAPITAL LIMITED is seeking a qualified quantitative development professional in Hong Kong to design and backtest models, build data pipelines, and audit AI-generated code for trading applications.

The role emphasizes quantitative modeling, robust testing, and rigorous documentation to ensure compliance and resilient systems in a fast-paced investment environment.

Qualifications

• Bachelor’s degree or higher in STEM from a top-tier institution (QS Top 100 preferred).
• Demonstrated track record in R&D, machine learning, data engineering, or automated system testing.
• Sound understanding of market mechanics, regulatory frameworks, and trading conventions across Hong Kong and U.S. capital markets.
• Analytical mindset with strong commercial awareness across targeted financial sectors and asset classes.
• Execution & resilience with autonomy in a high-intensity, tech-driven investment environment.

Responsibilities

• Model & Prototype Development: Co-design, prototype, and backtest quantitative models, MVPs, and automated trading tools.
• Data Engineering & Testing: Build robust data pipelines; conduct white-box testing, unit testing, and edge-case validation for critical financial systems.
• AI-Assisted Workflow & Code Audit: Review, benchmark, and audit code generated through LLMs/agentic coding tools to ensure algorithmic correctness and safety.
• Technical Documentation & Governance: Maintain architecture documentation, model validation reports, and audit trails to support deployment and regulatory compliance.

Skills

Statistical analysis

Data mining

Financial/econometric modeling

Python

R

SQL

Google Apps Script (GAS)

LLM-assisted rapid prototyping

Adaptability

Education

Bachelor’s degree in STEM

Tools

Python

R

SQL

Google Apps Script (GAS)

Job description

• Model & Prototype Development: Co-design, prototype, and rigorously backtest quantitative models, Minimum Viable Products (MVPs), and automated trading tools.
• Data Engineering & Testing: Build and optimize robust data pipelines; conduct rigorous white-box testing, unit testing, and edge-case validation for critical financial systems.
• AI-Assisted Workflow & Code Audit: Review, benchmark, and audit code generated through LLMs/agentic coding tools to ensure strict algorithmic correctness, execution safety, and system resilience.
• Technical Documentation & Governance: Maintain clear, comprehensive architecture documentation, model validation reports, and audit trails to support continuous deployment and regulatory compliance.

• Key Responsibilities

  • Model & Prototype Development: Co-design, prototype, and rigorously backtest quantitative models, Minimum Viable Products (MVPs), and automated trading tools.
  • Data Engineering & Testing: Build and optimize robust data pipelines; conduct rigorous white-box testing, unit testing, and edge-case validation for critical financial systems.
  • AI-Assisted Workflow & Code Audit: Review, benchmark, and audit code generated through LLMs/agentic coding tools to ensure strict algorithmic correctness, execution safety, and system resilience.
  • Technical Documentation & Governance: Maintain clear, comprehensive architecture documentation, model validation reports, and audit trails to support continuous deployment and regulatory compliance.

  Technical Requirements

  • Quantitative Foundations: Solid grounding in statistical analysis, data mining, and financial/econometric modeling.
  • Programming Proficiency: High proficiency in Python, R, SQL, or Google Apps Script (GAS).
  • AI & Agentic Development: Hands-on experience with modern AI agent frameworks, prompt engineering, and LLM-assisted rapid prototyping workflows ("vibe coding").
  • Agility & Continuous Learning: Strong intellectual agility with a proven ability to master and adopt emerging technologies and frameworks quickly.

  Qualifications

  • Academic Background: Bachelor’s degree or higher in a STEM discipline (Computer Science, Mathematics, Statistics, Engineering, or related quantitative field) from a top-tier institution (QS Top 100 preferred).
  • Domain Experience: Demonstrated track record in R&D, machine learning, data engineering, or automated system testing.
  • Market Acumen: Sound understanding of market mechanics, regulatory frameworks, and trading conventions across Hong Kong and U.S. capital markets.
  • Analytical Mindset: Exceptional problem-solving capabilities with keen commercial awareness across targeted financial sectors and asset classes.
  • Execution & Resilience: Proven dedication to long-term R&D initiatives, with the autonomy and drive to excel in a high-intensity, technology-driven investment environment.