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Trading Analytics Developer, Quantitative Trading
Hong Kong, Hong Kong SAR
Trading – Quant Front Office /
Full-time /
Hybrid
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The Quant Trading team is responsible for trading and managing risks associated with different crypto products, including spots and derivatives. The team develops and implements trading strategies in fast-paced and complex trading environments.
We are seeking an experienced Trading Analytics Developer to join our Quant Trading team and play a pivotal role in advancing our data and AI infrastructure. This role combines traditional quantitative development with cutting-edge AI platform engineering, focusing on building robust, scalable systems that serve both data analytics and artificial intelligence workloads. The ideal candidate will bridge the gap between high-performance trading systems and modern AI capabilities, ensuring reliability, performance, and actionable insights across both domains.
Core Responsibilities
- Data Platform & Analytics
- Design, build, and operate high throughput batch and streaming data pipelines using Kafka, Flink, and ETL technologies
- Develop and optimize analytical data models for time-series, financial metrics, and trading activity
- Implement and manage analytical databases (ClickHouse, MongoDB, BigQuery, Snowflake, or similar) with cost-aware architecture
- Build idempotent data pipelines with robust backfill and reconciliation capabilities
- Create comprehensive monitoring for data quality, freshness, and pipeline reliability
- AI Platform Development
- Design, build, and operate internal AI platforms serving multiple trading teams
- Develop vector search systems with optimized HNSW indexing and hybrid retrieval capabilities
- Implement evaluation frameworks for retrieval quality (Recall@K, MRR, nDCG) and RAG systems
- Build reusable AI tooling including standardized RAG pipelines, prompt management, and self-service workflows
- Create and maintain agent systems using modern frameworks (LangGraph, A2A, MCP) with focus on controllability and auditability
Technical Requirements
- Mandatory Foundations
- 5+ years production experience with both Python and Java in high-performance environments
- Strong software engineering fundamentals: system design, data structures, algorithms, data integrity, accuracy and performance optimization
- Expertise in Linux, Github, and modern CI/CD practices
- Proven experience with AWS cloud services and Kubernetes orchestration
- Comfort working with large-scale, complex datasets in financial/trading contexts
- Data Platform Expertise
- Advanced SQL with window functions and query optimization, realtime data synchronization together with database design and infrastructure support
- Experience with data workflow and messaging orchestration (Airflow, Jenkins, AMPS etc.)
- Metric design and implementation for trading analytics (PnL, risk, balance and trade reconciliation, backfill and performance tuning)
- Time-series data visualization with Grafana, TradingView and BI tools
- Kafka, Flink, and event processing in production environments
- AI Platform Capabilities
- Vector search system design and optimization (recall/latency/memory trade-offs)
- Retrieval system evaluation methodologies and quality frameworks
- RAG pipeline architecture and optimization techniques
- LLMOps practices including model lifecycle and prompt management
- Experience with AI agent frameworks in production settings like A2A and MCP
- LangGraph / LangChain to build AI workflow and to connect AI models with data and tools to create smarter applications.
Preferred Qualifications
- Financial/Trading Domain
- Experience in trading systems, quantitative finance, or financial technology
- Understanding of market data, data subscription using Rest API / Web Socket
- Knowledge of cryptocurrency markets, defi, and related technologies
- Professional Attributes
- Excellent problem-solving skills with ability to perform under pressure
- Strong communication skills for cross-team collaboration
- Proactive approach to system reliability and performance optimization
- Continuous learning mindset in rapidly evolving AI/ML landscape
- Balance of practical engineering rigor with innovative solution development
Life @ Crypto.com
Empowered to think big. Try new opportunities while working with a talented, ambitious and supportive team.
Transformational and proactive working environment. Elevate employees to find thoughtful and innovative solutions.
Growth from within. We help to develop new skill-sets that would impact the shaping of your personal and professional growth.
Work Culture. Our colleagues are some of the best in the industry; we are all here to help and support one another.
One cohesive team. Engage stakeholders to achieve our ultimate goal - Cryptocurrency in every wallet.
Are you ready to kickstart your future with us?
Benefits
Competitive salary
Medical insurance package with extended coverage to dependents
Attractive annual leave entitlement including: birthday, work anniversary
Work Flexibility Adoption. Flexi-work hour and hybrid or remote set-up
Aspire career alternatives through us. Our internal mobility program can offer employees a diverse scope.
Work Perks: crypto.com visa card provided upon joining
Our Crypto.com benefits packages vary depending on region requirements, you can learn more from our talent acquisition team.
About Crypto.com:
Founded in 2016, Crypto.com serves more than 150 million customers and is the world's fastest growing global cryptocurrency platform. Our vision is simple: Cryptocurrency in Every Wallet™. Built on a foundation of security, privacy, and compliance, Crypto.com is committed to accelerating the adoption of cryptocurrency through innovation and empowering the next generation of builders, creators, and entrepreneurs to develop a fairer and more equitable digital ecosystem.
Learn more at https://crypto.com.
Crypto.com is an equal opportunities employer and we are committed to creating an environment where opportunities are presented to everyone in a fair and transparent way. Crypto.com values diversity and inclusion, seeking candidates with a variety of backgrounds, perspectives, and skills that complement and strengthen our team.
Personal data provided by applicants will be used for recruitment purposes only.
We may use artificial intelligence tools to analyze the content of your Resume/CV against the specific requirements for the position. The purpose is to support our recruitment team in reviewing applications more effectively. These tools assist our recruitment team in their evaluation of your application by providing recommendations, but they do not replace human judgment. Final hiring decisions are ultimately made by humans who consider the insights generated by the tools along with other relevant information. If you would like more details about how your personal information is processed, please contact us.
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What is a quantitative career?
A quantitative career is a profession that involves using mathematical, statistical, and computational techniques to solve problems and make decisions in a wide range of industries, including finance, engineering, healthcare, and technology
A quantitative career in Web3 involves using mathematical, statistical, and computational techniques to analyze and optimize decentralized finance (DeFi) protocols, blockchain networks, and other Web3 applications
Some examples of quantitative careers include:
- Quantitative Analyst: A professional who uses mathematical models and statistical analysis to identify and quantify risks and opportunities in financial markets.
- Data Scientist: A professional who analyzes complex data using statistical methods, machine learning, and other techniques to help organizations make data-driven decisions.
- Actuary: A professional who uses mathematical models and statistical analysis to assess risk and uncertainty in the insurance and finance industries.
- Quantitative Developer: A professional who develops and implements quantitative models and trading strategies for financial institutions and other organizations.
- Operations Research Analyst: A professional who uses mathematical and statistical techniques to optimize complex systems, such as supply chains, transportation networks, and manufacturing processes.