大手証券会社でのQuantitative Developerの求人

Responsibilities：
Basel III (FRTB) is an industry-wide regulatory initiative to which includes proposals to introduce a framework for Market Risk. We require an experienced Java and Python quantitative developer to join the Market Risk team to work on FRTB model development. Our tech stack is predominantly distributed Java and Python services, with relational and distributed databases, GemFire as a caching layer and ActivePivot for real-time interrogation of aggregated risk metrics. We use Python ecosystem for rapid prototyping, distributed computing and development of market risk models. We are also building out a Hadoop store of market risk data, which incorporates Dremio for data querying and both Arrow and Parquet as columnar data formats.
The successful candidate will work on the build-out of new functionality for FRTB. They will need to work closely with risk quants, and to work with developers and BAs across regions. They will be expected to adapt to new technologies quickly, and to work across a range of data-oriented tech including ActivePivot, Hadoop, and Public Cloud Compute Technologies like AWS. They will have to analyse requirements, propose designs (for example for new services), circulate them for feedback, break the design down into tasks and execute them. The ability to be clear and precise in both written and verbal communication is also critical.

Requirements:
Mandatory

・Masters or Bachelor’s degree in Computer Science and/or Financial Engineering
・Java core language (Java 8+), multi-threading, performance optimisation
・Numerate
・Python (experience w/ pandas, numpy, dask, Prefect)
・Market Risk general concepts
・Comfortable building distributed computing systems, worked with compute grid tech
・Excellent communication skills in English and preferably in Japanese
・Ability to multi-task, and work towards tight deadlines


Preferred

・Experience of working either with Methodology/Quants or on pricing/risk models
・Market Risk VaR methodology, P&L Explains/Predict, FRTB, SBA, IMA
・Distributed, service-oriented architectures
・Hadoop, Dremio and the related ecosystem
・ActivePivot, GemFire or similar in-memory cache/aggregation technologies
・AWS Technologies
・Experience working with FO quantitative pricing libraries and Compute Grid Technologies