Quantamental Implementation Analyst
Quantamental Implementation Analyst
We are currently working with a Tier 1 hedge fund that is looking to hire a Quantamental Implementation Analyst in Hong Kong.
About the Role: We are seeking a passionate and skilled Quantamental Implementation Analyst to join our dynamic team. The ideal candidate will be enthusiastic about data and adept at building efficient data processing pipelines. This role involves working on multiple projects simultaneously, requiring a pragmatic and commercially minded approach to problem-solving. The successful candidate will contribute to core technology and data processes within the quantamental team.
Key Responsibilities:
Technology and Data Platform Development:
- Collaboratively develop resilient, transparent, and flexible data platform tools for quantamental research.
- Build infrastructure solutions for data pipelines at various scales.
- Design and implement high-performing and robust libraries of reusable tools for systematic research processes, including signal construction, backtesting, and diagnostics.
- Collect requirements, design, and implement reporting and visualization tools for use by quantamental and fundamental team members.
- Provide ad hoc development support to individual researchers, customizing tools for specific needs.
Data Management:
- Monitor and maintain the integrity of data flows to ensure timely access to clean data for researchers.
- Act as the first point of contact for data-processing-related issues with upstream teams.
- Liaise with the Data Engineering team to onboard and maintain data sources.
- Implement business logic for cleaning, validating, and augmenting traditional and alternative data to ensure suitability for core research.
Process Management:
- Ensure proper knowledge management within the team, including sharing data, key analyses, insights, and reusable code.
- Oversee the code review process to ensure proper version control, use of CI/CD pipelines, and process portability.
- Promote best practices in production application deployments and integrations with trade execution teams.
Requirements:
- 2+ years of professional software engineering experience, including prospective graduates.
- Exceptional problem-solving skills and quick learning ability.
- Strong multitasking capabilities.
- Focus on quality control, improvements, and adherence to agreed processes and controls.
- Ability to interact with and influence various stakeholders of different tenures and expertise levels.
- Proficiency in Python and data science libraries (pandas, NumPy).
- Understanding of SQL, NoSQL, column-stores, and document-store databases, and their interrelation with data types and APIs.
- Experience with cloud, container, and microservice infrastructures (e.g., Kubernetes, Docker, Helm, AWS, GCP).
- Pragmatic approach to problem-solving.
- Passion for data and building efficient data processing pipelines.
- Ability to identify potential risks to processes and build analytics and monitoring for mitigation.
- Ability to see the big picture at a global process level and not get lost in technical details.
- Ability to work well within a multi-stakeholder, multi-project environment.
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