Asset Management- Equities Quantitative Developer - Vice President/Associate

JPMorgan Chase & Co.; City of Rochester (NY); On-site; USD 130,000 - 190,000; Full time

Job summary

JPMorgan Chase & Co. in Rochester, NY seeks a Quantitative Developer/Engineer to design, develop, deploy, and operate data pipelines and quant applications that impact alpha generation for asset management clients.

You will translate research agendas into production-ready systems and collaborate with researchers to advance the research agenda. The role includes building sophisticated ML pipelines, onboarding data sets, and automating reporting for portfolio managers, with a focus on production

Qualifications

• 3+ years of experience in relevant fields.
• Degrees in Computer Science or Engineering.
• Proficiency in Python programming, with multithreading and multiprocessing familiarity; database management across SQL, NoSQL, and Snowflake; familiarity with ETL pipelines; and AWS application architecture.
• Familiarity with Git-based version control and collaborative workflows.
• Experience with Airflow or similar workflow orchestration tools for production data pipelines.
• Statistics and finance knowledge, especially in equity asset management or quantitative investing.
• Good communication and project management skills.
• Experience building sophisticated automated processes and technology infrastructure.

Responsibilities

• Lead management of production processes and daily communication with technology team to ensure production pipeline operates as expected.
• Translate research models into production processes.
• Automate generation of reports for portfolio managers.
• Enhance efficiency of research processes, including alpha model estimation and backtesting pipelines.
• Onboard new data sets and conduct exploratory analysis while managing existing datasets.
• Lead development of end-to-end ML pipelines suitable for production deployment.
• Conduct research projects in quantitative equity investment.

Skills

Python

SQL

NoSQL

Snowflake

ETL

AWS

Airflow

Git

Multithreading

Multiprocessing

ML pipelines

Production pipelines

Quant finance

Communication

Education

B.S. in Computer Science or Engineering

Tools

Airflow

Snowflake

AWS

Job description

Role Summary

The Quantitative Developer/Engineer is expected to design, develop, deploy and operate innovative data pipelines and quant applications to impact the team's alpha generation for asset management clients. You will help implement the research agenda of the U.S. Disciplined Core Equity group and enhance the production processes. The developer will also work on research projects in partnership with other researchers.

Job Responsibilities

• Lead the management of production processes and daily communication with technology team to ensure production pipeline is functioning as expected
• Translate research models into production processes
• Automate generation of reports for portfolio managers
• Enhance the efficiency of the research processes such as improving alpha model estimation and optimized backtesting pipeline
• Onboard new data sets and conduct exploratory analysis and manage existing data sets used in research
• Lead development of highly sophisticated end-to-end ML pipelines in research, which can be deployed in production environment easily
• Conduct research projects in quantitative equity investment

Required qualifications, capabilities and skills

• 3+ years of experience in relevant fields
• Degrees in Computer Science or Engineering
• Proficiency in Python programming, including familiarity with multithreading and multiprocessing; database management experience across SQL, NoSQL, and Snowflake; familiarity with ETL pipelines; and experience architecting applications within AWS
• Familiarity with Git-based version control and collaborative software development workflows
• Experience with Airflow or similar workflow orchestration tools for production data pipelines
• Statistics and finance knowledge, especially within equity asset management, quantitative equity investing, or portfolio construction
• Good communication and project management skills
• Experience in building sophisticated automated processes and technology infrastructure

Preferred qualifications, capabilities and skills

• Experience with tax-aware long-short optimizations and implementation
• Experience with vendor optimization platforms and packages, such as MSCI Barra Open Optimizer, for portfolio construction, tax optimization, and optimization workflows
• Experience in designing processes used in financial services
• Knowledge of Machine Learning, Natural Language Processing, and other unstructured data
• Experience in building pipelines for ML inference based on text, timeseries or financial data
• Familiarity with statistical packages such as Matlab