Quantitative Engineer

Summit Securities Group•New York, NY

1d•$150,000 - $250,000•Hybrid

About The Position

Exceptional trading emerges where human intuition meets frictionless experimentation. Our platform and processes enable traders to rapidly investigate ideas, identify emergent patterns, and convert insights into live strategies. This synthesis creates a flywheel of discovery—the key to our pursuit of excellence. Summit Securities Management LLC seeks a Quantitative Engineer to serve as a key driver in the research, development and implementation of our systematic trading environment and tooling.

Requirements

Must have a Bachelor’s degree or foreign equivalent in Computer Science, Financial Engineering, Electrical Engineering, Statistics, or a related quantitative field.
Must have 5 years of experience in the position offered or related in a quantitative research or development role.
Must have 5 years of experience with: Implementing applications utilizing Python and its scientific computing stack including Pandas and NumPy for data analysis, modeling, and building production systems
Must have 5 years of experience with: Building and delivering quantitative development projects including backtesting frameworks, data systems, and execution tools
Must have 5 years of experience with: Leading the end-to-end development of critical business platforms from initial architecture and design through to deployment and ongoing maintenance
Must have 5 years of experience with: Working with a variety of financial datasets and databases including index data and market data
Must have 5 years of experience with: Engineering high-performance ingestion libraries and APIs to access normalized index data
Must have 5 years of experience with: Building real-time P&L and risk metric infrastructure across all desk trading positions.

Responsibilities

Own the end-to-end development of components that enable the business’ success, from building the foundational data pipelines and back testing to financial risk management tools.
Design and build high-performance libraries and API’s that ingest, normalize and provide access to large scale financial datasets such as index data and market data.
Architect and implement flexible, scalable back testing platforms to rigorously evaluate and calibrate new trading strategies across various historical regimes.
Engineer the complete order generation, execution and position management tooling required to run the strategies in a live trading environment, accounting for capital constraints and corporate actions.
Build and maintain the infrastructure and interactive dashboards required to monitor the real-time P&L and risk exposures of live trading portfolios.
Apply knowledge of systematic trading such as statistical arbitrage, risk analytics, and execution research.