Senior Quantitative Developer

3 weeks ago


Boston, Massachusetts, United States Selby Jennings Full time

Responsibilities:

  • Developing and maintaining Python libraries crucial for supporting investment research production processes.
  • Designing and implementing software solutions to enhance our data science technology stack.
  • Creating financial data APIs and numerical APIs.
  • Utilizing cloud and distributed computing technologies.
  • Implementing performance enhancements in data analysis and numerical programming code.
  • Conducting Proof of Concepts (POCs) to assess new technologies and libraries within the PyData ecosystem.
  • Collaborating with software engineers to devise data feeds for new sources from third-party vendors.
  • Leading and executing major components or features in our data science platform.
  • Mentoring, training, and providing technical guidance to junior team members regarding design and coding standards.
  • Engaging in other projects based on personal experience and interests.

Qualifications:

  • A degree in computer science from an accredited educational institution.
  • Strong analytical and problem-solving abilities.
  • Proficiency in Python programming with experience in implementing production-grade code.
  • Familiarity with Object-Oriented Programming (OOP) principles, data structures, and numerical algorithms.
  • Knowledge of various data storage technologies including RDBMS, S3, columnar databases, and NoSQL databases.
  • Experience with distributed computing frameworks such as Spark, Dask, or HPC.
  • Understanding or 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 mandatory).
  • Excellent communication skills.
  • High energy levels and a strong work ethic.

Additionally, experience with any of the following would be beneficial:

  • Technologies like Hadoop, Spark, Kafka, and related tools.
  • Proficiency in Unix/Linux system tools and environments.
  • Basic understanding of unit testing, continuous integration, DevOps, and containerization.
  • Interactive data visualization and dashboard development.


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