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:
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Writing and maintaining Python libraries that supports the investment research production processes
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Designing and creating software to enhance our data science technology stack
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Design and implement financial data APIs and numerical APIs
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Apply cloud and distributed computing technologies
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Implementing performance improvements in our data analysis and numerical programming code
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Running POCs to evaluate new technologies and libraries in the PyData ecosystem
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Working with software engineers to design feeds for new data sources from third-party vendors
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Propose and lead implementations of major components or features in our data science platform
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Mentor, train and provide technical guidance to junior team members in design and coding standards
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Other projects based on experience and interest.
Qualifications:
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An undergraduate or graduate degree from an educational institution in computer science
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Strong analytical and problem solving skills
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Expert programming skills in Python, experience implementing production-grade Python code
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Experience in OOP paradigms, data structures, and numerical algorithms
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Data storage: RDBMS, S3, columnar databases, NOSQL databases
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Distributed computing: Spark, Dask, or HPC
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Understanding/interest in probability and statistics, including linear regression and time-series analysis
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Curiosity and a willingness to learn new technologies
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Interest in financial markets (prior experience not required)
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Excellent communication skills
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High energy and strong work ethic
In addition, experience with any of the following would be valuable:
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Hadoop, Spark, Kafka, and related technologies
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Unix/Linux system tools and environment
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Basic familiarity with unit testing, continuous integration, DevOps, containerization
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Interactive data visualization and dashboards
We maintain a friendly, team-oriented environment and place a high value on professionalism, attitude and initiative.
Top Skills
What We Do
Arrowstreet Capital is a Boston-based investment manager that provides global and international equity investment strategies and fund products to institutional investors such as pension plans, endowments, foundations, and registered/unregistered commingled investment funds.
We offer a select range of global equity investment strategies managed as long-only, alpha extension and long/short utilizing a broad range of instruments, including swaps and futures. Our investment process utilizes quantitative methods that focus on identifying and incorporating investment signals into our proprietary return, risk and transaction cost models. Our investment approach involves creating and investing in diversified equity portfolios. We utilize a structured investment process that attempts to add value relative to a client specific benchmark. This involves identifying opportunities across companies, sectors and countries by evaluating a diverse set of fundamental and market-based predictive factors. Portfolios are constructed through the use of a mean variance optimizer and proprietary risk and transaction cost models.
Arrowstreet Capital manages approximately $100 billion for over 200 client relationships in North America, the United Kingdom, Europe and the Asia-Pacific regions.
