AM Quantitative Analyst II

Fidelity•Boston, MA

3d•Onsite

About The Position

Leads development of cross-regional quantitative models, integrating equity, factor, macroeconomic, and alternative data-driven signals into unified research frameworks. Oversees validation and stability testing of next‑generation alpha models, including regime‑shift analysis, stress scenarios, factor decay studies, and production‑grade sensitivity testing. Applies advanced econometrics, data science, and programming skills using Python, R, MATLAB, and SQL to analyze financial data and build visualization dashboards. Designs and implements advanced machine learning (ML) methodologies (ensemble models, nonlinear optimization routines, and Bayesian inference systems) to enhance predictive accuracy and robustness. Analyzes financial or operational performance of companies facing financial difficulties to identify or recommend remedies. Develops portfolio construction engines capable of optimizing across multiple objectives (risk, capacity, turnover, and ESG constraints) while supporting multi-strategy workflows.

Requirements

Bachelor’s degree in Accounting, Economics, Finance, Statistics, Mathematics, Financial Engineering, or a closely related field (or foreign education equivalent) and five (5) years of experience as an AM Quantitative Analyst II (or closely related occupation) investigating large structured and novel data sources to generate alpha, using Python, R, MATLAB and SQL in a Linux environment.
Master’s degree in Accounting, Economics, Finance, Statistics, Mathematics, Financial Engineering, or a closely related field and three (3) years of experience as an AM Quantitative Analyst II (or closely related occupation) investigating large structured and novel data sources to generate alpha, using Python, R, MATLAB and SQL in a Linux environment.
Demonstrated Expertise (“DE”) applying portfolio optimization techniques to construct long-only portfolios with normal and customized dynamic constraints, using Gurobi or Cplex.
DE constructing and analyzing options-implied volatility surfaces across maturities and strikes -- building alpha signals on the volatility surface and stock options trading flow dynamics.
DE developing non-linear signal aggregation framework to combine alpha sources, using ML models -- Neural Network via Tensorflow and Keras in Python.
DE designing and operationalizing systematic investment strategies for new active equity product launches, including defining the investment universe, development of signal weighting framework, and specifying portfolio construction rules, using R and Python.

Responsibilities

Improves performance of stock selection models through idea generation, empirical analysis, and back-testing.
Implements quantitatively based equity models, transaction cost modeling, risk mitigation as well as evaluates and develops new risk models.
Investigates large structured and alternative data sources to generate alpha, designs research studies, and simulates portfolios to enhance investment strategies.
Develops signals based on equity option characteristics that capture the informational spillover from the options market to the equity market.
Leads exploratory research into new investment products leveraging proprietary alpha and risk models.
Monitors, measures, and attributes portfolio risks and returns.
Guides the integration of quantitative tools into trading systems, to enable automated signal deployment, intraday model refresh cycles, and scalable execution optimization processes.
Evaluates and enhances cross-team research infrastructure.
Advises on computational frameworks, cloud migration initiatives, and performance tuning for large-scale processing.
Actively participates in the team’s research agenda from idea generation, research design, back-testing and portfolio simulations, to implementation.
Collaborates with research, technology, and trading teams to integrate quantitative methods into the investment process and improve infrastructure and tools.
Advises clients on aspects of capitalization -- amounts, sources, or timing.