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As a Quant Developer at AHL you will be working hand-in-hand with our Quant Researchers. Your challenges will be varied, and will involve implementing new trading strategies, building new research frameworks and quant libraries, prototyping new data feeds, development of new portfolio construction techniques or building risk analysis tools
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 + Kubernetes for containerisation, OpenStack for our private cloud, Ansible for architecture automation, and Slack for internal communication. But our technology list is never static: we constantly evaluate new tools and libraries.
Technology and Business Skills
We strive to hire only the brightest and best and most highly skilled and passionate technologists.
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.
An excellent understanding of financial markets and instruments
Knowledge and experience of fixed income products or volatility trading.
Experience of quantitative or automated 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.
Strong academic record and a degree with high mathematical or computing content e.g. Computer Science, Mathematics, Engineering or Physics from a leading university
Craftsman-like approach to building software; takes pride in engineering excellence and instils these values in others
Focused on delivering value to the business with relentless efforts to improve process
Strong interpersonal skills; able to establish and maintain a close working relationship with quantitative researchers, traders and senior business people alike
Confident communicator; able to argue a point concisely and deal positively with conflicting views.
Intellectually robust with a keenly analytic approach to problem solving
Self-organised with the ability to effectively manage time across multiple projects and with competing business demands and priorities.
Demonstrable passion for technology e.g. personal projects, open-source involvement.