Quant Developer - Research Engineering

Chicago Trading Company

  • Chicago, IL
  • 16 days ago

    Highlights

    Partner with quantitative researchers and traders to understand their research questions, and design the data, tooling and compute to answer them. You will partner directly with quants across the firm, and own the infrastructure that turns research ideas into results that can be trusted and repeated.

    Numbers & Facts

    LocationChicago, IL

    Description

    As a Quantitative Developer you will work at the boundary between quantitative research and production engineering, building the systems and datasets our researchers and traders depend on. You will partner directly with quants across the firm, and own the infrastructure that turns research ideas into results that can be trusted and repeated.

    What You'll Do

    • Partner with quantitative researchers and traders to understand their research questions, and design the data, tooling and compute to answer them
    • Build, operate and optimise the pipelines and execution frameworks behind our research and backtesting
    • Take research prototypes into production, with the reliability, reproducibility and observability that production requires
    • Own foundational shared datasets used across multiple desks, including their quality and timeliness
    • Profile and optimise performance-critical numerical code, balancing runtime against compute and storage cost
    • Migrate existing research pipelines onto modern data platforms, and improve the process for the migrations that follow
    • Build evaluation tooling that lets researchers judge model performance
    • Collaborate across the wider data and technology organisation to improve the platform every desk builds on

    What We're Looking For

    • Strong Python at production depth - numpy and pandas fluency, vectorisation, and profiling
    • Working proficiency in C++
    • Solid quantitative foundations, particularly statistics - probability, regression and time series with the judgement to distinguish signal from noise
    • Strong software design skills and hands-on experience building and operating data pipelines at scale
    • The interpersonal skills to work directly with quants and traders, and to turn an ambiguous research need into a concrete design
    • A pragmatic bias toward getting something correct and useful into researchers' hands quickly

    Nice to Haves

    • Experience in options trading, market making, or another trading environment
    • Backtesting, simulation, or research-platform infrastructure
    • Hands-on experience with a major cloud provider and/or HPC managers
    • Experience with Apache Iceberg or similar technology
    • Experience with high volume market data capture
    • C++ Template meta programming experience

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