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Quantitative Developer

C2R Ventures
Boston
1 week ago
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Our client, a global Quant Trading shop with more than 170bb in managed assets, and under 300 employees, is seeking a talented Quant Developer join the firms Research group. The development team within Research is responsible for the tools, APIs, libraries and software engineering techniques to support faster generation, evaluation and Productionization of investment ideas.

You will be tasked with building out a next-generation Research data platform leveraging open-source, cloud and distributed computing technologies. You will work on high-impact projects that are quickly adopted and drive change across the team.

This is a collaborative, data-driven, intellectually rigorous team responsible for coming up with investment ideas, codifying those ideas into signals, back-testing the signals, and producing return, risk and trading cost forecasts based on the signals to drive trading decisions.

Responsibilities include, but are not limited to:

  • Writing and maintaining Python libraries that supports the investment research production processes
  • Designing and creating software to enhance our data science technology stack
  • Design and implement financial data APIs and numerical APIs
  • Apply cloud and distributed computing technologies
  • Implementing performance improvements in our data analysis and numerical programming code
  • Running POCs to evaluate new technologies and libraries in the PyData ecosystem
  • Working with software engineers to design feeds for new data sources from third-party vendors
  • Propose and lead implementations of major components or features in our data science platform
  • Mentor, train and provide technical guidance to junior team members in design and coding standards
  • An undergraduate or graduate degree from an educational institution in computer science
  • Strong analytical and problem-solving skills
  • Expert programming skills in Python, experience implementing production-grade Python code
  • Experience in OOP paradigms, data structures, and numerical algorithms
  • Distributed computing: Spark, Dask, or HPC
  • Understanding/interest in probability and statistics, including linear regression and time-series analysis
  • Curiosity and a willingness to learn new technologies
  • Interest in financial markets (prior experience not required)

Valuable, and nice to have:

  • Hadoop, Spark, Kafka, and related technologies
  • Unix/Linux system tools and environment
  • Basic familiarity with unit testing, continuous integration, DevOps, containerization
  • Interactive data visualization and dashboards

Seniority level

  • Seniority levelMid-Senior level

Employment type

  • Employment typeFull-time

Job function

  • Job functionEngineering, Finance, and Information Technology
  • IndustriesSoftware Development and Financial Services

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