What you'll do:

• The end-to-end research, development, and maintenance of investment platform, data and algorithms
  
• Take part in building out the R&D back testing and simulation engines
• Thoroughly vet investment algorithmic results
• Contribute to the research data platform design
• Investigate datasets for use in new or existing algorithms
• Participate in agile development practices
• Liaise with stakeholders to gather & understand the functional requirements
• Take part in code reviews ensuring quality meets highest level of standards
• Develop software 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, software, processes, procedures, and methods
• Collaborate with technology teams to ensure appropriate requirements, standards, and integration

What makes you a great fit:

• Experience in a quant research & development role
• Proficient in Python, Git and Jira
• Knowledge in SQL and database development (PostgreSQL is a plus)
• Understanding of R and RMarkdown is a plus
• Bachelor’s degree in computer science, computational mathematics, or financial engineering
• Master’s degree or advanced training is a strong plus
• 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.)