Quantitative Equity Research Analyst

4 weeks ago


Boston, Massachusetts, United States Fidelity Investments Full time
Job Description:

Position Overview:
Fidelity Investments is seeking a highly skilled Quantitative Equity Research Analyst to join our team. As a key member of our research group, you will be responsible for investigating large structured and novel data sources to generate alpha using Python, R, MATLAB, SQL, VBA, and Tableau. You will integrate quant research, technology, and trading using FactSet, Bloomberg, Axioma, and Barra.

Key Responsibilities:
Develop and maintain quantitative stock selection models globally. Participate in the team's research agenda and take responsibility for the full life cycle of each project from idea generation, research design, back-testing, and portfolio simulations to implementation. Enhance the investment process by investigating techniques to improve portfolio construction and optimization. Implement quantitatively based equity models, transaction cost modeling, and risk mitigation. Evaluate and develop new risk models. Drive improvements to quant infrastructure and technology platform. Collaborate in the development or testing of new analytical software to ensure compliance with user requirements, specifications, or scope. Prepare requirements documentation for use by software developers.

Requirements:
Bachelor's degree in Engineering, Physics, Accounting, Economics, Finance, Statistics, Mathematics, or a closely related field and five years of experience as a Quantitative Equity Research Analyst investigating large structured and novel data sources to generate alpha using Python, R, MATLAB, or SQL in a Linux environment. Alternatively, Master's degree in Engineering, Physics, Accounting, Economics, Finance, Statistics, Mathematics, or a closely related field and three years of experience as a Quantitative Equity Research Analyst investigating large structured and novel data sources to generate alpha using Python, R, MATLAB, or SQL in a Linux environment. Alternatively, PhD in Quantitative and Computational Finance, Physics, Financial Mathematics, Computer Science, Mathematics, Accounting, Engineering, Statistics, or a closely related field and no experience.

Skills and Knowledge:

Candidate must also possess:
Demonstrated expertise in designing, creating, analyzing, and validating quantitative equity investment strategies (alpha and risk models) using macro and micro economic reasoning, econometrics analysis, advanced mathematical, statistical, and machine learning techniques using TensorFlow or PyTorch. Conducting and streamlining quantitative research processes on signals and factors which predict future stock returns using data science techniques, big data extraction, transformation, and load (ETL), and web scraping using HTCondor or Slurm. Developing medium to high frequency equity and FX market-predictive signals with shorter investment horizons and processing high frequency market data using tick level time series analytic platforms OneTick. Utilizing economics, linear algebra, numerical analysis, and other mathematical optimization techniques to improve existing portfolio construction methodology, incorporating multi-period optimization techniques combining fast and slow predictive signals with different investment horizons, and setting up and solving portfolio optimization problems using Mosek or Gurobi.

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