Salary
≈ $198k – $427k per year (Estimated)
Location
In office (New York)
Seniority
Architect · 3+ years exp
Visa
H-1B filings in 12 months: 3,429 · for this role: 451 · green card filings: 933
Confirmed on the employer's own hiring board on Oct 25, 2026. First seen by Alion on Aug 11, 2026. JPMorganChase scores A on the Alion truth index.
Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.
Backed by Balderton Capital, Radical Partners, team@irregular
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
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