Lord Abbett & Co. seeks Quantitative Analysts in Jersey City, New Jersey.• Produce performance attribution and portfolio analysis reports for client requests coming through Client Services, as well as for internal clients such as Portfolio Managers, Research Analysts, and Investment Risk Managers.• Work with Client Services teams such as Product Strategy and Investment Strategy to customize analyses for client needs.• Work with PMs, Research Analysts, and Risk Managers in Investments to develop valuable performance attribution reports and analyses to better inform the investment process.• Understand, maintain, improve and build quantitative tools essential to investment process.• Work with the quantitative team, fundamental investments analysts and portfolio managers to express their investment views, philosophies and processes through the use of innovative tools and methodologies.• Work with the team to enhance scale, rigor, and capacity of the quantitative research process through software development best practices.• Take part in developing new models, custom analytics, and technologies that enhance the investment process and the investment team’s productivity.• Have excellent analytical and problem-solving skills with a keen attention to detail and an inclination to validate everything.• Perform empirical research to uncover insights from both traditional and alternative data.• Incorporate machine learning techniques to generate quant equity signals.• Collaborate on improving analytic library, data sourcing and end-user reporting.• Propose and implement ideas that make quantitative equity resources more valuable to the broader firm.Requires a Master's degree in Statistics, Computer Science, or a related field plus 2 years of related experience. Requires 2 years of experience with the following: Technical and analytical communication skills; equity and fixed income markets, securities, asset classes, and analytics; FactSet, FactSet PA, Bloomberg PORT or PORT+.40 hours/week $190,000 - $210,000. per year. Applicants who are interested in this position may apply online at www.jobpostingtoday.com (Ref: # 60905).