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Chase · 3 months ago

Quant Researcher & Developer

1 Liberty Sq Fl 2, Boston, MA, 02109, US

Full-time

Onsite

Mid Level

$150K/yr - $224K/yr

Chase is a leading financial technology company focused on breaking down barriers to financial progress. The Quant Researcher & Developer will research, implement, test, and maintain investment algorithms for wealth management firms, contributing to the development of optimization models and collaborating with technology teams to ensure integration and standards are met.

BankingFinancial Services

Responsibilities

The 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

Contribute to the research data platform design

Investigate datasets for use in new or existing algorithms

Participate in agile practices

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 aggressive experimentation of cutting-edge hardware, advanced analytics, machine learning techniques, and other methods

Collaborate with technology teams to ensure appropriate requirements, standards, and integration

Qualification

PythonQuantitative analysisStatistical techniquesMachine learningCommercial optimizersSQLGitJiraFinancial capital marketsHustleAgilityAttention to detailCommunicationProblem-solving

Required

Experience in a quantitative role

Proficient in Python, Git and Jira

Professional experience with commercial optimizers (Gurobi, CPLEX) is a big plus

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

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.)

Experience in direct-indexing products is a big plus

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

Knowledgeable in SQL

Agility: Able to shift gears and react quickly to timely requests

Hustle: Self-motivated, proactive, responsive-ability to think strategically but also willing to dig into the details and tactics