Arrowstreet Capital
Senior Quantitative Developer
Arrowstreet Capital, Boston, Massachusetts, us, 02298
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 processesDesigning and creating software to enhance our data science technology stackDesign and implement financial data APIs and numerical APIsApply cloud and distributed computing technologiesImplementing performance improvements in our data analysis and numerical programming codeRunning POCs to evaluate new technologies and libraries in the PyData ecosystemWorking with software engineers to design feeds for new data sources from third-party vendorsPropose and lead implementations of major components or features in our data science platformMentor, train and provide technical guidance to junior team members in design and coding standardsOther projects based on experience and interest.Qualifications:
An undergraduate or graduate degree from an educational institution in computer scienceStrong analytical and problem solving skillsExpert programming skills in Python, experience implementing production-grade Python codeExperience in OOP paradigms, data structures, and numerical algorithmsData storage: RDBMS, S3, columnar databases, NOSQL databasesDistributed computing: Spark, Dask, or HPCAbility to drive technical workUnderstanding/interest in 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 skillsHigh energy and strong work ethicIn addition, experience with any of the following would be valuable:
Hadoop, Spark, Kafka, and related technologiesUnix/Linux system tools and environmentBasic familiarity with unit testing, continuous integration, DevOps, containerizationInteractive data visualization and dashboardsPeople management experience
We maintain a friendly, team-oriented environment and place a high value on professionalism, attitude and initiative.
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 processesDesigning and creating software to enhance our data science technology stackDesign and implement financial data APIs and numerical APIsApply cloud and distributed computing technologiesImplementing performance improvements in our data analysis and numerical programming codeRunning POCs to evaluate new technologies and libraries in the PyData ecosystemWorking with software engineers to design feeds for new data sources from third-party vendorsPropose and lead implementations of major components or features in our data science platformMentor, train and provide technical guidance to junior team members in design and coding standardsOther projects based on experience and interest.Qualifications:
An undergraduate or graduate degree from an educational institution in computer scienceStrong analytical and problem solving skillsExpert programming skills in Python, experience implementing production-grade Python codeExperience in OOP paradigms, data structures, and numerical algorithmsData storage: RDBMS, S3, columnar databases, NOSQL databasesDistributed computing: Spark, Dask, or HPCAbility to drive technical workUnderstanding/interest in 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 skillsHigh energy and strong work ethicIn addition, experience with any of the following would be valuable:
Hadoop, Spark, Kafka, and related technologiesUnix/Linux system tools and environmentBasic familiarity with unit testing, continuous integration, DevOps, containerizationInteractive data visualization and dashboardsPeople management experience
We maintain a friendly, team-oriented environment and place a high value on professionalism, attitude and initiative.