Quantitative Developer - Data Platform & Risk Analytics
at Capula Investment Management
Posted 16 hours ago
No clicks
- Compensation
- Not specified
- City
- London, New York City, Singapore, Hong Kong, Tokyo, Geneva, Abu Dhabi
- Country
- United Kingdom, United States, Singapore, China, Japan, Switzerland, United Arab Emirates
Currency: Not specified
Capula Investment Management is seeking a quantitative developer to build and operate data platforms and risk analytics systems, enabling P&L, VaR, scenarios and risk exposure management across portfolios. The role collaborates with quants, traders and risk managers to deliver reliable BAU services in Python while designing low-latency C# components, and to deliver greenfield builds powering reporting with Python, Excel and web tools. You will manage data at scale (SQL, Parquet, in-memory stores), design schemas and indexing, deploy on Linux in AWS with CI/CD and Infrastructure-as-Code, and own end-to-end delivery of risk systems used daily. Ability to evaluate modern columnar technologies and vectorized execution for sub-second analytics on high-volume tick data will be encouraged.
Description
The Firm
Capula Investment Management is a leading global quantitative hedge fund managing over $30 billion in assets. We are headquartered in London and have offices in New York, Singapore, Hong Kong, Tokyo, Geneva and Abu Dhabi. We manage absolute return, enhanced fixed income, macro and alpha strategies for a diversified group of investors worldwide. Capula invests in a broad universe of asset classes, including fixed income, equities, currencies and commodities, as well as derivatives related to these asset classes.
The Role
We are looking for a quantitative developer to build and operate data platforms and risk analytics systems to manage P&L, VaR, scenarios, and risk exposures across our portfolios. You’ll work closely with quantitative researchers, traders and risk managers to deliver reliable BAU services in Python while designing next‑generation, low‑latency components in C#. You will contribute to both evolutionary improvements and greenfield builds that power reporting and analysis through Python, Excel, and web-based tools.
What you’ll do
- Own BAU production services in Python running in Docker: monitor, troubleshoot, and continuously improve reliability, test coverage, and deployment pipelines.
- Manage and optimize data at scale: ingest, store, and serve large financial data sets in SQL, DuckDB/Parquet, and in‑memory databases; design schemas, partitioning, and indexing for multi‑dimensional access e.g., by instrument, portfolio, scenario and time‑series.
- Design a low‑latency alternative path in C#: build ingestion and access layers optimized for speed (efficient serialization, columnar/contiguous memory access, in‑memory stores/caches, async I/O), and integrate them with existing risk/pricing workflows.
- Propose cutting‑edge solutions: evaluate modern columnar technologies, in‑memory query engines, and vectorized execution; prototype approaches for sub‑second analytics on high‑volume tick and end‑of‑day data.
- Deliver greenfield projects end‑to‑end—from design and build to production rollout—while maintaining critical risk systems used daily by the business.
- Deploy and operate on Linux in AWS (EKS, ECS, EC2, S3) with CI/CD and Infrastructure‑as‑Code.
Duties & Responsibilities
- Development & maintenance of risk systems and data services used for P&L, VaR, scenarios, and exposure reporting.
- Performance engineering: query tuning, profiling (CPU/IO), memory‑aware data layouts, in‑memory caching strategies, and fast analytics.
- Collaboration with quants, risk, and trading; clear communication of trade‑offs and design decisions.
