Looking for an experienced, detail-oriented quantitative developer to assist with the development and deployment of our industry-leading mathematical/statistical models for real-time, pre- and post-trade transaction cost analysis, and making them available for trading applications.
The successful candidate joins a strong team that conducts trading-related development by applying principles of scientific computing, numerical optimization as well as analytical and programming skills. We create actionable products that improve decision-making for equity, FX, and other asset classes.
Responsibilities will include:
Leverage scientific computing skills and utilize robust numerical optimization algorithms for trading applications
Integrate our new models to a platform powered by a relational time series database framework with in-memory computation engine.
Develop reusable common framework components for trading analytics development
Assist in migrating of existing financial analytics and models to a KDB/q environment
Automate the validation and QA of new models and their applications in the trading process
Conduct critical comparison of alternative data sources
Lead other researchers and developers in using cutting-edge open-source data science tools applicable to data analysis, model deployment, and data visualization.
Effectively document the use cases, requirements and architectural specifications related to the models and their applications
Maintain and support the existing research tools, infrastructure and products
Qualified candidates will have:
Advanced degree in a quantitative field (e.g. computer science, operations research, engineering, applied mathematics, physics, computational finance)
Experience with scalable software development and deployment
In depth knowledge of algorithms and data structures
Strong programming skills in Python (including scikit-learning) as well as experience with relational databases
knowledge of fixed income markets with emphasis on trading-related aspects
Ability to effectively use the Linux platform for development and high-throughput data processing
Previous experience with statistical, machine learning and optimization techniques
Ability to effectively communicate and collaborate with multi-office/region teams
Experience with C++ or other programming languages, and familiarity with KDB/q would be helpful, but is not required
Job Type: Full-time
Pay: $170,000.00 - $210,000.00 per year
Compensation package:
Work Location: In person