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Quantitative Developer

Boston, MA, United States

Role Summary

We are looking for an experienced Quant Developer with Python experience , to join our Research group. We are 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. We maintain a friendly, team-oriented environment and place a high value on professionalism, attitude and initiative.

Our 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.

As a Quantitative Developer, you will help build our 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.

Responsibilities:

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

Other projects based on experience and interest.

Qualifications: 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

Data storage: RDBMS, S3, columnar databases, NOSQL databases

Distributed computing: Spark, Dask, or HPC

Ability to drive technical work

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)

Excellent communication skills

High energy and strong work ethic

In addition, experience with any of the following would be valuable: 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

People management experience

We maintain a friendly, team-oriented environment and place a high value on professionalism, attitude and initiative.

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