Quantitative Researcher


: $107,230.00 - $200,310.00 /year *

Employment Type

: Full-Time


: Scientific Research

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Job Description
Our global quantitative research and development team consists of self-motivated, articulate and highly skilled professionals. A unique blend of people with different skillset - from finance, through software engineering to mathematics and physics. We are looking for a Quantitative Researcher to join us.
As a Quantitative Researcher you will be responsible for
Performing quantitative research in order to extend the coverage and improve the existing parts of the FactSet Multi-Asset Class Risk models, Focusing on Fixed Income/Credit spread factor and risk models.
Design and prototype the respective quantitative solution using python, R or Excel depending on the use case.
Contribute to the risk factor model library used across FactSet risk research and development team.
Design tests and proceduresto validate model performance in terms of proper handling the systematicrisk exposures and specific risk.
Collaborate with teams of quantitative researchers, quantitative developers, software engineers, product development and strategy to transform business requirements into a high quality risk solution.
Job Requirements
PhD or Master Degree in Science, Technology, Engineering or Mathematics
Background in probability and statistics/calculus/optimization and numerical methods
Minimum 5 years of experience with at least three of the following;
1)Fixed income factor models and risk models
2)Multi-asset class risk models
3)Linear factor modeling and model selection techniques (cross-sectional models)
4)Time series analysis and financial time series forecasting using statistical methods
5)Strong programming skills using any of the languages Python, R, C++, or Java.
Ability to handle large data sets in a numerical computation oriented development environment
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
Any of the following will be considered an advantage
Experience with Java
Algorithms development, optimizing and scaling up time consuming code
Knowledge in SQL, preferably on MSSQL Server
University or high school math contests
VEVRAA Federal ContractorRequest Priority Protected Veteran & Disabled Referrals for all of our locations within the stateThe EEO is the Law poster is available here.FactSet Research Systems Inc. endeavors to make our website accessible to any and all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process, please contact Jennifer Passeck, Lead Recruiting Specialist, Human Resources at +1 (203) ###-#### or ...@factset.com.Equal Opportunity Employment PolicyIt is the policy of FactSet Research Systems Inc. (\"FactSet\") to provide equal employment and advancement opportunities to all qualified employees and applicants for employment regardless of their race, color, religion, sex, age, sexual orientation, gender identity or expression, national origin, physical or mental disability, genetic information, protected veteran status, pregnancy, military or military reserve obligations, or any other class or status protected by law. This policy applies to all policies and procedures related to recruitment, hiring, training, promotion, compensation, benefits, transfer, discharge, and other terms and conditions of employment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability or protected veteran status. If you have questions concerning this policy, please contact the Human Resources department at +1 (203) ###-####.
Associated topics: circuit, c++, c c++, electrical engineering, electronic engineering, information technology, machine learning, photonics, radar, software * The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.

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