Vice President; Sr Quant Inv Analyst at Bank of America

What you'd actually do

Create, enhance, implement, and maintain quantitative models for a broad range of investment analytics which include, but are not limited to, goals-based investment and wealth management, quantitative asset allocation, portfolio construction and analytics, product modeling, quantitative investment strategy development and implementation, risk and return forecasting, performance attribution, and other wealth management analytics.

Design and deliver robust and innovative quantitative investment strategies, rules-based model portfolios, and validated analytical models at scale to help our clients achieve their financial goals across all GWIM channels (Merrill, Edge, Institutional, Private Bank, Retirement & Personal Wealth Services).

Develop and manage stakeholder relationships across the Bank with a wide variety of partners.

Focus on model building and refinement and/or portfolio construction.

Demonstrate outstanding coding, debugging, and analytical skills.

Communicate clearly in an audience-appropriate manner to influence via expertise to earn the trust of key stakeholders by translating complex quantitative concepts into common-sense terms and thinking.

Skills

Required

Master's degree or equivalent in Computer Science, Computer Information Systems, Management Information Systems, Engineering (any), or related
3 years of experience in the job offered or a related Quantitative occupation
Developing non-Gaussian stochastic models (jump-diffusion processes, Lévy processes, fractional Brownian)
Developing dynamic Bayesian inference techniques (Markov Chain Monte Carlo methods)
Python
R
MATLAB
Bayesian inferences
alpha factor research
convex and non-convex portfolio optimization
Solving large-scale, non-convex optimization problems (Interior-Point Methods, Trust-Region Methods, Quadratic Programming, Mixed-Integer Programming)
Gurobi
Spectral decomposition (Diffusion Maps, Kernel Principal Component Analysis, Non-Negative Matrix Factorization)
Optimizing utility functions (constant relative risk aversion, S-curve/kinked utility)
Econometric modelling
Generalized Method of Moments
Kalman filters
dynamic Bayesian methods
Vector Auto-Regression

What the JD emphasized

Developing non-Gaussian stochastic models specifically jump-diffusion processes, Lévy processes, and fractional Brownian including dynamics of wealth accumulation and consumption incorporating entropy-based measures

Developing dynamic Bayesian inference techniques including Markov Chain Monte Carlo methods for state-space models

Using tools and libraries in Python, R and MATLAB for Bayesian inferences, alpha factor research, and convex and non-convex portfolio optimization

Solving large-scale, non-convex optimization problems including Interior-Point Methods, Trust-Region Methods, Quadratic Programming, and Mixed-Integer Programming involving discrete variables and use of Gurobi

Employing spectral decomposition specifically Diffusion Maps, Kernel Principal Component Analysis, and Non-Negative Matrix Factorization to financial data

Optimizing utility functions (constant relative risk aversion, S-curve/kinked utility as well as econometric modelling) including Generalized Method of Moments, Kalman filters, dynamic Bayesian methods, and Vector Auto-Regression

Job Description:

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.

Being a Great Place to Work is core to how we drive Responsible Growth. This includes our commitment to being an inclusive workplace, attracting and developing exceptional talent, supporting our teammates’ physical, emotional, and financial wellness, recognizing and rewarding performance, and how we make an impact in the communities we serve.

Bank of America is committed to an in-office culture with specific requirements for office-based attendance and which allows for an appropriate level of flexibility for our teammates and businesses based on role-specific considerations.

At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!

**Responsibilities **

Create, enhance, implement, and maintain quantitative models for a broad range of investment analytics which include, but are not limited to, goals-based investment and wealth management, quantitative asset allocation, portfolio construction and analytics, product modeling, quantitative investment strategy development and implementation, risk and return forecasting, performance attribution, and other wealth management analytics.
Design and deliver robust and innovative quantitative investment strategies, rules-based model portfolios, and validated analytical models at scale to help our clients achieve their financial goals across all GWIM channels (Merrill, Edge, Institutional, Private Bank, Retirement & Personal Wealth Services).
Develop and manage stakeholder relationships across the Bank with a wide variety of partners.
Focus on model building and refinement and/or portfolio construction.
Demonstrate outstanding coding, debugging, and analytical skills.
Communicate clearly in an audience-appropriate manner to influence via expertise to earn the trust of key stakeholders by translating complex quantitative concepts into common-sense terms and thinking.

Required Skills & Experience

Master's degree or equivalent in Computer Science, Computer Information Systems, Management Information Systems, Engineering (any), or related: and
3 years of experience in the job offered or a related Quantitative occupation.
Must include 3 years of experience in each of the following:
Developing non-Gaussian stochastic models specifically jump-diffusion processes, Lévy processes, and fractional Brownian including dynamics of wealth accumulation and consumption incorporating entropy-based measures;
Developing dynamic Bayesian inference techniques including Markov Chain Monte Carlo methods for state-space models;
Using tools and libraries in Python, R and MATLAB for Bayesian inferences, alpha factor research, and convex and non-convex portfolio optimization;
Solving large-scale, non-convex optimization problems including Interior-Point Methods, Trust-Region Methods, Quadratic Programming, and Mixed-Integer Programming involving discrete variables and use of Gurobi;
Employing spectral decomposition specifically Diffusion Maps, Kernel Principal Component Analysis, and Non-Negative Matrix Factorization to financial data; and,
Optimizing utility functions (constant relative risk aversion, S-curve/kinked utility as well as econometric modelling) including Generalized Method of Moments, Kalman filters, dynamic Bayesian methods, and Vector Auto-Regression.

If interested apply online at www.bankofamerica.com/careers or email your resume to bofajobs@bofa.com and reference the job title of the role and requisition number.

EMPLOYER: Merrill Lynch

Shift:

1st shift (United States of America)

**Hours Per Week: **

Pay Transparency details

US - NY - New York - ONE BRYANT PARK - BANK OF AMERICA TOWER (NY1100)

Pay and benefits information

Pay range

$230,000.00 - $253,000.00 annualized salary, offers to be determined based on experience, education and skill set.

Discretionary incentive eligible

This role is eligible to participate in the annual discretionary plan. Employees are eligible for an annual discretionary award based on their overall individual performance results and behaviors, the performance and contributions of their line of business and/or group; and the overall success of the Company.

Benefits

This role is currently benefits eligible. We provide industry-leading benefits, access to paid time off, resources and support to our employees so they can make a genuine impact and contribute to the sustainable growth of our business and the communities we serve.