The 55ip Quant team is looking for a quantitative professional to research, implement, test, and maintain the core algorithms of its technology-enabled investment platform for large investment advisory (RIA) & wealth management firms

As a Research Analyst at JP Morgan Chase within the Asset and Wealth Management and the 55ip Quant team, you will have the opportunity to research, implement, test, and maintain the core algorithms of our technology-enabled investment platform for large investment advisory (RIA) & wealth management firms. If you have a background in statistical modules using software design constructs and tools, are motivated, a problem solver, and an effective team player looking to make a significant impact in supporting research projects, this role could be a perfect fit for you. This position offers the chance to grow as an independent researcher.

Job responsibilities

Involve in end-to-end research, development, and maintenance of investment algorithms Contribute to development and maintenance of optimization models, take part in building out the research and development framework Thoroughly vet investment algorithmic results and contribute to the research data platform design Investigate datasets for use in new or existing algorithms, participate in agile practices and liaise with stakeholders to gather & understand the functional requirements Take part in research & code reviews , develop code using high quality standards and best practices, conduct thorough end-to-end unit testing, and provide support during testing and post go-live Support research innovation through the creative and thorough experimentation of cutting-edge hardware, advanced analytics, machine learning techniques, and other methods Collaborate with technology teams to ensure appropriate requirements, standards, and integration

Required qualifications, capabilities, and skills

Experience in a quantitative role Proficient in Python, Git and Jira Master’s degree in computer science, computational mathematics, or financial engineering  Excellent mathematical foundation and hands-on experience working in the finance industry Proficient in quantitative, statistical, and ML/AI techniques and their implementation using Python modules such as Pandas, NumPy, SciPy, SciKit-Learn, etc. Strong communication (written and oral) and analytical problem-solving skills Strong sense of attention to detail, pride in delivering high quality work and willingness to learn An understanding of or exposure to financial capital markets, various financial instruments (such as stocks, ETFs, Mutual Funds, etc.), and financial tools (such as Bloomberg, Reuters, etc.) Knowledgeable in SQL

 

Preferred qualifications, capabilities, and skills

 

Professional experience with commercial optimizers (Gurobi, CPLEX) is a big plus Able to shift gears and react quickly to timely requests Self-motivated, proactive, responsive-ability to think strategically but also willing to dig into the details and tactics Understanding of LaTeX and/or RMarkdown is a plus