We're looking to expand our Fixed Income Quantitative Research group with a newly created position reporting to the Director of Fixed Income Quantitative Research. The group is responsible for all quantitative research and model development for the firm’s taxable and tax free fixed income portfolios, with a current total AUM in excess of $125 billion. The group develops and maintains relative value tools as well as models used in portfolio construction and risk management, and it has a significant involvement in product design. The quant group is part of the Investment organization and both physically and organizationally located close to traders and portfolio managers.
• Carry out statistical analysis in support of investment recommendations
• Develop and implement new models of fixed income security valuation
• Work with end users and IT to design applications for research, trading and risk management
• Maintain, support and enhance existing tools and models
• PhD in a highly quantitative field
• 1-3 years of relevant experience
• Knowledge of financial markets/products and finance theory
• Strong command of a scripting language like Python, Matlab or R
• Knowledge of statistical methods and related software
• Experience with numerical programming including optimization
• Strong English communication skills, both written and spoken
• Experience creating production quality code (including testing and documentation)
Founded in 1929, Lord Abbett is a leading asset manager with approximately $160 billion in assets under management. We share a passion for excellence in serving our diverse range of clients – individuals, advisors, and institutions across the globe who rely on us to deliver innovative investment solutions that help them secure stronger financial futures. We are looking for candidates who value trust, intellectual curiosity, and teamwork as much as we do.
We are an equal opportunity employer and value diversity at our firm. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.