for the global Python community

AHL Quant Platform Developer

Posted by Man AHL on Fri, 14 Jul 2017
Contract type: permanent. Location: London, England

Contact

Name: Milly Parrott

Overview

As a Quant Platform Developer at AHL you will be building the tools, frameworks, libraries and applications which power our Quantitative Research and Systematic Trading. This includes responsibility for the continued success of “Raptor”, our in-house Quant Platform, next generation Data Engineering, and evolution of our production Trading System as we continually expand the markets and types of assets we trade, and the styles in which we trade them. Your challenges will be varied and might involve building new high performance data acquisition and processing pipelines, cluster-computing solutions, numerical algorithms, position management systems, visualisation and reporting tools, operational user interfaces, continuous build systems and other developer productivity tools.

The Team

Quant Platform Developers at AHL are all part of our broader technology team, members of a group of over sixty individuals representing eighteen nationalities. We have varied backgrounds including Computer Science, Mathematics, Physics, Engineering - even Classics - but what unifies us is a passion for technology and writing high-quality code.

Our developers are organised into small cross-functional teams, with our engineering roles broadly of two kinds: “Quant Platform Developers” otherwise known as our “Core Techs”, and “Quant Developers” which we often refer to as “Sector Techs”. We use the term “Sector Tech” because some of our teams are aligned with a particular asset class or market sector. People often rotate teams in order to learn more about our system, as well as find the position that best matches their interests.

Our Technology

Our systems are almost all running on Linux and most of our code is in Python, with the full scientific stack: numpy, scipy, pandas, scikit-learn to name a few of the libraries we use extensively. We implement the systems that require the highest data throughput in Java. For storage, we rely heavily on MongoDB and Oracle.

We use Airflow for workflow management, Kafka for data pipelines, Bitbucket for source control, Jenkins for continuous integration, Grafana + Prometheus for metrics collection, ELK for log shipping and monitoring, Docker for containerisation, OpenStack for our private cloud, Ansible for architecture automation, and HipChat for internal communication. But our technology list is never static: we constantly evaluate new tools and libraries.

Working Here

AHL has a small company, no-attitude feel. It is flat structured, open, transparent and collaborative, and you will have plenty of opportunity to grow and have enormous impact on what we do. We are actively engaged with the broader technology community.

  • We host and sponsor London’s PyData and Machine Learning Meetups
  • We open-source some of our technology. See our github
  • We regularly talk at leading industry conferences, and tweet about relevant technology and how we’re using it. See @manahltech.

We’re fortunate enough to have a fantastic open-plan office overlooking the River Thames, and continually strive to make our environment a great place in which to work.

  • We organise regular social events, everything from photography through climbing, karting, wine tasting and monthly team lunches
  • We have annual away days and off-sites for the whole team
  • We have a canteen with a daily allowance for breakfast and lunch, and an on-site bar for in the evening
  • As well as PC’s and Macs, in our office you’ll also find numerous pieces of cool tech such as light cubes and 3D printers, guitars, ping-pong and table-football, and a piano.

Technology and Business Skills

Essential

  • Exceptional technology skills; recognised by your peers as an expert in your domain
  • A proponent of strong collaborative software engineering techniques and methods: agile development, continuous integration, code review, unit testing, refactoring and related approaches
  • Expert knowledge in one or more programming languages, preferably Python, Java and/or C/C++
  • Proficient on Linux platforms with knowledge of various scripting languages
  • Strong knowledge of one or more relevant database technologies e.g. Oracle, MongoDB
  • Proficient with a range of open source frameworks and development tools e.g. NumPy/SciPy/Pandas, Pyramid, AngularJS, React
  • Familiarity with a variety of programming styles (e.g. OO, functional) and in-depth knowledge of design patterns.

Advantageous

  • An excellent understanding of financial markets and instruments
  • Experience of front office software and/or trading systems development e.g. in a hedge fund or investment bank
  • Expertise in building distributed systems with service-based or event-driven architectures, and concurrent processing
  • A knowledge of modern practices for data engineering and stream processing
  • An understanding of financial market data collection and processing
  • Experience of web based development and visualisation technology for portraying large and complex data sets and relationships
  • Relevant mathematical knowledge e.g. statistics, asset pricing theory, optimisation algorithms.