Principal Front Office Engineer, Multi-Asset Risk Solutions - Investments Technology

Excellent problem-solving skills, with the ability to think critically, independently, and act with minimal handholding. Effective communication skills, with the ability to clearly articulate complex ideas and analysis to both technical and non-technical stakeholders. Strong attention to detail, organization, and the ability to manage multiple tasks and priorities in a fast-paced environment. Full-stack development knowledge with a minimum of 5 years professional experience programming in Python demonstrating the ability to write efficient and robust code able to process and analyze large financial datasets. Experience with key Python Libraries (pandas, NumPy) required Experience in front-end development and user experience (UX) design required; experience with Pythonic front-end and data visualization libraries (e.g., Plotly, Dash) preferred. Experience using Agentic Programming tools (Github Copilot, Claude) required. Proven ability to design, build, and scale application systems in data-rich environments including custom AI tools. Strong SQL skills required with a familiarity of financial data platforms (such as Bloomberg, FactSet, Aladdin, eFront, Moodys), financial databases, and data manipulation techniques preferred. Experience with statistical and time-series data analysis using pythonic libraries (such as Scikit-Learn, SciPy, cvxpy) is preferred. Solid understanding of financial markets and multi-asset investment risk domain. Practical experience in developing and maintaining models, tools, and reports that showcase a deep understanding of quantitative techniques, methods, statistics and econometrics Excellent problem-solving skills, with the ability to think critically, independently Effective communication skills, with the ability to clearly articulate complex ideas and analysis to both technical and non-technical stakeholders. Strong attention to detail, organization, and the ability to manage multiple tasks and priorities in a fast-paced environment. Full-stack development knowledge with a minimum of 5 years professional experience programming in Python demonstrating the ability to write efficient and robust code able to process and analyze large financial datasets. Experience with key Python Libraries (pandas, NumPy) required Experience in front-end development and user experience (UX) design required; experience with Pythonic front-end and data visualization libraries (e.g., Plotly, Dash) preferred. Experience using Version Control (Git) required. Proven ability to design, build, and scale application systems in data-rich environments. Strong SQL skills required with a familiarity of financial data platforms (such as Bloomberg, FactSet, Aladdin, eFront), financial databases, and data manipulation techniques preferred. Experience with statistical and time-series data analysis using pythonic libraries (such as Scikit-Learn, SciPy, cvxpy) is preferred. Solid understanding of financial markets/investments and risk Practical experience in developing and maintaining models, tools, and reports that showcase a deep understanding of quantitative techniques, methods, statistics and econometrics In-depth knowledge of diverse and emerging technologies, architectural concepts and principles A deep understanding of layered solutions and designs Awareness of policies regarding security and privacy Understanding of backlog tracking, burndown metrics and incremental delivery A Bachelor's or Master's degree in a technical or business discipline, or equivalent experience