Arrowstreet Capital
Quantitative Developer, Associate
Arrowstreet Capital, Boston, Massachusetts, us, 02298
Team Overview
We are looking for Quantitative Developers 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 quantitative 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.
ResponsibilitiesYour responsibilities are expected to grow in line with your experience and abilities. Depending on your competitive advantages, typical responsibilities may include:Writing and maintaining Python and R code that supports the investment research production processesDesigning and creating software to enhance our data science technology stackPerforming ad-hoc exploratory statistical analysis across multiple large complex data sets from a variety of structured and unstructured sourcesImplementing performance improvements in our data analysis and numerical programming codeRunning POCs to evaluate new technologies and libraries in the PyData ecosystemStaying up to date on the PyData ecosystem and evaluating new libraries and toolsWorking with software engineers to design feeds for new data sources from third-party vendorsQualifications
An undergraduate or graduate degree from an educational institution in computer science with a quantitative application such as mathematics and/or finance, or vice versa - a quantitative degree with a computer science applicationDemonstrated professional or academic success (recent graduates are encouraged to apply)Strong analytical, quantitative, and problem solving skillsExperience implementing production-grade Python code for a data analytic business, preferably in investment managementExpert programming skills in Python with pandas and numpyExpertise in OOP paradigms, data structures, and numerical algorithmsUnderstanding of probability and statistics, including linear regression and time-series analysisCuriosity and a willingness to learn new technologiesInterest in financial markets (prior experience not required)Excellent communication skills, including data visualizationHigh energy and strong work ethicIn addition, experience with any of the following would be valuable:
Some experience programming in R with tidyverse packagesHigh-performance computingDistributed computingHadoop, Spark, Kafka, and related technologiesSQLUnix/Linux system tools and environmentBasic familiarity with unit testing, continuous integration, DevOps, containerizationInteractive data visualization and dashboards
We maintain a friendly, team-oriented environment and place a high value on professionalism, attitude and initiative.
We are looking for Quantitative Developers 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 quantitative 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.
ResponsibilitiesYour responsibilities are expected to grow in line with your experience and abilities. Depending on your competitive advantages, typical responsibilities may include:Writing and maintaining Python and R code that supports the investment research production processesDesigning and creating software to enhance our data science technology stackPerforming ad-hoc exploratory statistical analysis across multiple large complex data sets from a variety of structured and unstructured sourcesImplementing performance improvements in our data analysis and numerical programming codeRunning POCs to evaluate new technologies and libraries in the PyData ecosystemStaying up to date on the PyData ecosystem and evaluating new libraries and toolsWorking with software engineers to design feeds for new data sources from third-party vendorsQualifications
An undergraduate or graduate degree from an educational institution in computer science with a quantitative application such as mathematics and/or finance, or vice versa - a quantitative degree with a computer science applicationDemonstrated professional or academic success (recent graduates are encouraged to apply)Strong analytical, quantitative, and problem solving skillsExperience implementing production-grade Python code for a data analytic business, preferably in investment managementExpert programming skills in Python with pandas and numpyExpertise in OOP paradigms, data structures, and numerical algorithmsUnderstanding of probability and statistics, including linear regression and time-series analysisCuriosity and a willingness to learn new technologiesInterest in financial markets (prior experience not required)Excellent communication skills, including data visualizationHigh energy and strong work ethicIn addition, experience with any of the following would be valuable:
Some experience programming in R with tidyverse packagesHigh-performance computingDistributed computingHadoop, Spark, Kafka, and related technologiesSQLUnix/Linux system tools and environmentBasic familiarity with unit testing, continuous integration, DevOps, containerizationInteractive data visualization and dashboards
We maintain a friendly, team-oriented environment and place a high value on professionalism, attitude and initiative.