MFS' Quantitative Solutions team has three primary areas of responsibility: 1) risk management for all MFS portfolios; 2) portfolio management for multi-asset class portfolios, including the Asset Allocation, Lifetime Target Date and Global Tactical Allocation products; and 3) portfolio management for equity portfolios that employ quantitative stock selection models, including Blended Research, Systematic Research, and PPS products. This internship is in quantitative equity research, working on topics related to the Blended Research portfolios and the stock selection models they employ.
As a summer intern in quantitative equity research, you will take on one or more projects related to MFS' stock selection models, portfolio construction strategies, research technology, or a combination of those topics. You will participate in the quant team's meetings and discussions, as well as appropriate fundamental research and portfolio management meetings. You will work independently but in consultation with quantitative analysts and portfolio managers. MFS will be evaluating for full time hires as Quantitative Research Associates from the Summer Internship program to start in 2025 following their graduation from college.
Job Responsibilities:
- Work within quantitative research team on projects related to development of quantitative alpha models and/or the technology underlying those subjects.
- Assist in the development and implementation of disciplined quantitative processes focused on alpha generation, portfolio construction and risk management.
- Effectively communicate results of processes and research.
- Assume additional projects and responsibilities as required.
Job Requirements:
- Rising Senior.
- Study focused in Finance, Economics, Mathematics, Computer Science, Engineering, or other quantitatively oriented discipline.
- Exceptional analytical skills, ability to assemble, clean and evaluate large datasets.
- Strong problem solving skills and the ability to work independently on complex projects.
- Proficiency in programming languages such as Python, R, or Matlab. Familiarity with SQL, Excel and financial data software such as Bloomberg or FactSet is a plus.
- Strong communication skills; both written and verbal.
- Attention to detail and commitment to accuracy.