Job description

Job Overview We are looking for an experienced Quantitative Developer, 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 5 years of experience working as a Quantitative Developer or a in a related role 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 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 The base salary range for this position is $170,000 - $325,000 per year. Arrowstreet Capital operates a robust talent acquisition program, and we also seek to compensate and reward our employees competitively within our industry and in line with our merit-based culture. Our approach to total compensation includes base salaries and annual discretionary bonuses, as well as a robust benefits package. The determination of a successful candidate’s base salary placement within the listed range will vary based on the candidate’s relevant experience and qualifications (which may also include relevant certifications, credentials and other education), the job responsibilities and scope, the commensurate resulting level of the position and other relevant factors. The listed range is also an estimate, and additional information regarding base salary and other elements of total compensation offered by Arrowstreet Capital to successful applicants will be communicated during the recruitment process. Arrowstreet Capital is a Boston-based systematic investment firm that manages global equity portfolios for institutional investors around the world. All qualified applicants will receive consideration for employment without regard to sex, race, color, religion, national origin, ancestry, genetic information, age, pregnancy, medical condition, disability, veteran or military status, marital status or any other characteristic protected by federal, state, or local law. Arrowstreet Capital is committed to working with and providing reasonable accommodations for qualified individuals with disabilities and disabled veterans. If you need a reasonable accommodation for any part of the employment process due to a disability, contact us to discuss the nature of your request and contact information.

Requirements

Must-haves

Job Overview
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.
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.
An undergraduate or graduate degree from an educational institution in computer science
5 years of experience working as a Quantitative Developer or a in a related role
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
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

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

python

Platform: workday
Effort: long