Quantitative Researcher – Full Valuation Risk

FactSet is a financial data and software company headquartered in Norwalk, CT with offices in 48 locations worldwide. As a global provider of financial information and analytics, FactSet helps the world’s best investment professionals outperform. More than 170,000 users across 7000+ clients stay ahead of global market trends, access extensive company and industry intelligence, and monitor performance with FactSet’s desktop analytics, mobile applications, and comprehensive data feeds. As of August 2023, annual subscription value reached $2.2 billion.

As part of FactSet’s Institutional Buy Side Middle Office Solutions Unit our Risk Quantitative Research and Development team (Risk QRD) is responsible for researching and developing FactSet’s in-house factor-based risk models. That includes linear factor models construction, risk factors multivariate distribution fitting and forecasting, among others. This is a global team that consists of self-motivated, articulate and highly skilled professionals. A unique blend of people with strong quantitative and technical skills.

Our team develops both new and existing in-house risk models which have downstream impact for many other systems and teams, including but not limited to: software engineering, product development, model validation, strategy, and sales. We continuously improve our risk models based on internal research, recent advances in the risk modeling, changing market environments, and the feedback from our clients and the users of the risk models.

FactSet’s Full Valuation MAC products offer a factor-based, full-valuation, multi-asset class solution that supports historical and parametric risk and risk budgeting, and stress testing. Designed for advanced client portfolios, these products cover over 50 security types, including equities, fixed income, and a wide range of vanilla and exotic derivatives.  The Full Valuation Risk Research team is dedicated to the research, prototyping, validation, testing, and support of these models.

Responsibilities:

As a Quantitative Researcher on this team, you will be primarily involved in the research and implementation of factor-based full-valuation multi-asset class risk models and stress scenarios. You will be required to:

• Research, prototype, develop, and support in Python the respective models and their main building blocks, such as risk factors' historical time series quality, consistency, and coverage; risk factors estimation and factor risk model construction; interpret and validate the resulting quantitative analytics and risk statistics.
• Analyze plausibility of both historical and multivariate Monte Carlo risk models’ scenarios, as well as historical and hypothetical stress scenarios. Fine-tune the definitions and parameters of the full-valuation models to improve their performance.
• Ensure the quality and consistency of risk models results for diverse multi-asset class portfolios through use of extensive model testing and documentation.
• Collaborate closely with global teams of quantitative researchers, software engineers, and product developers to ensure the timely and high-quality delivery of the end product.

The ideal candidate for this role will be eager to both teach and learn. Being successful on this team is not possible without curiosity, clear communication, and willingness to break down and solve complex problems.

Requirements:

• Advanced Degree in Science, Technology, Engineering or Mathematics.
• 2+ years of experience in the field of quantitative analysis, data science or machine learning.
• Strong knowledge of probability theory, statistics, linear algebra, and numerical methods.
• Experience working with large data sets, statistical data analysis, building multivariate statistical models.
• Good programming skills using any of the languages Python, R, C++, or Java.
• Analytical thinking and problem solving.
• Natural curiosity and creativity.
• Agile, action-oriented, quick thinker: you can deliver preliminary results fast by making simplifying assumptions and take time to dive deeper if our business priorities allow and if the problem demands more scientific rigor.

Highly Desired:

• Experience with Python and/or Java.
• Familiarity with databases and SQL for data manipulation, extraction, and analysis.
• Interest in financial markets and risk modeling.
• Experience with collaborative development best practices, such as roadmap planning, VCS, automated testing, code reviews, etc.
• University or high school math contests.

We offer:

A place in the team developing our own world-class risk solutions where everyone’s contributions to the team and product success are visible, and the product, passion and hard work are recognized and valued.

A friendly business casual atmosphere in a workplace that consists of diverse talents and working environment driven by challenges, recognition, and rewards. Nice office location and compensation package as well as flexible working hours and hybrid work model are also included.

Apply today and become part of the successful FactSet Risk Quantitative Research and Development Team!