Associate, Research

About the Role

Morgan Stanley is seeking an Associate, Research in New York, New York to provide financial analysis reports and materials for individual industries and sector-specific companies.

Key Responsibilities

• Provide financial analysis reports and materials for individual industries and sectors-specific companies.
• Analyze industry data to develop an industry-specific vision.
• Update and create financial models.
• Analyze emerging trends in an industry or macro-economy.
• Assess relative stock valuations and review findings with team as well as internal and external clients.
• Build relationships with global colleagues, salespeople, traders and external investing clients.
• Combine quantitative processes with fundamental insights to identify industry key performance indicators, develop sector-specific signals, build conviction on a call, predict stock returns, and track company-specific risks.
• Develop, back-test, and implement statistics models, machine learning, and AI to test the efficacy of sector data.
• Explore and evaluate alternative data to gain insights into new alpha and develop trading strategies.
• Build tools to query, clean, analyze raw data through databases, and work closely with technology team to ensure data quality and delivery.
• Publish leading research insight notes and present at industry conferences.
• Actively source new ideas and collaborate with other research teams.
• Collaborate with sales and marketing, providing quant proof statements to both internal and external clients.
• Telecommuting permitted up to 1 day per week.

Requirements & Tech Stack

• Deep Neural Networks
• Long Short-Term Memory (LSTM)
• Convolutional Neural Networks
• Tree-based Methods including Decision Trees and Random Forest
• Principal Component Analysis (PCA) and Dimensionality reduction
• Lasso Regression, Ridge Regression, and Logistic Regression
• Classification including k-Nearest Neighbor
• Time-series Modelling including Autoregressive Integrated Moving Average (ARIMA)-based methods
• Financial Modelling
• Statistical Analysis
• Big Data Analysis
• Forecasting
• Probability Theory
• Data Set Evaluation
• Back-testing
• Geospatial Analysis
• Python
• Git
• Linux
• Q/KDB
• SQL
• MS Office Suite
• Investment Report Writing
• Microeconomics
• Macroeconomics
• Stochastic Calculus

Qualifications

• Requires a Master’s in Computational Finance, Financial Engineering, or a related field of study.