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As a Research Analyst at JP Morgan Chase within the Asset and Wealth Management Technology and 55ip 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 & 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. As a quantitative professional, your role will involve research, implement, test, and maintain the core algorithms of its technology-enabled investment platform for large investment advisory & wealth management firms.
Job responsibilities
Involves end-to-end research, development, and maintenance of investment algorithms
Contributes to development and maintenance of optimization models, take part in building out the research and development framework
Vets investment algorithmic results thoroughly and contributes to the research data platform design
Investigates datasets for use in new or existing algorithms, participate in agile practices and liaise with stakeholders to gather & understand the functional requirements
Takes 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
Supports research innovation through the creative and bold experimentation of cutting-edge hardware, advanced analytics, machine learning techniques, and other methods
Collaborates with technology teams to ensure appropriate requirements, standards, and integration
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 2+ years applied experience
Master’s degree in computer science, computational mathematics, or financial engineering
Experience in a quantitative role with proficiency in Python, Git and Jira
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
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.)
Strong sense of attention to detail, pride in delivering high quality work and willingness to learn
Preferred qualifications, capabilities, and skills
Professional experience with commercial optimizers (Gurobi, CPLEX) is a big plus
Experience in direct-indexing products 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