Data Scientist AVP

The Machine Learning team in the Wealth Management (WM) Analytics & Data (A&D) organization at Morgan Stanley is dedicated to delivering machine learning solutions to a wide range of internal stakeholders in wealth management. Our team specializes in a variety of applied research areas, including recommender systems, client personalization, marketing propensity models, and asset and client attrition models. We provide machine learning solutions to a diverse group of internal stakeholders, delivering delightful new experiences to over 15 million WM clients.

You will:

·       Design and develop end-2-end machine learning solutions to address business opportunities in Wealth Management, delivering tangible business outcomes.

·       Strive to develop and experiment with State-of-the-Art algorithms.

·       Validate the machine learning models in collaboration with the validation team to ensure the accuracy and reliability of ML models.

·       Deploy the machine learning models in production environments, in collaboration with the MLOps team, and monitor their performance.

·       Conduct A/B tests to demonstrate efficacy of ML solutions.

·       Participate in code reviews from both sides of the process.

·       Build, grow, and establish partnerships with business stakeholders, marketing as well as with our Risk, Legal, and Compliance divisions.

·       Create presentations to effectively showcase modelling results to stakeholders and the team.

·       A Master’s (PhD can be a plus) degree in Computer Science, Engineering, Mathematics, or a related quantitative field.

·       At least 3 years of professional experience in Machine Learning.

·       Demonstrated breadth and depth in knowledge and applications of machine learning algorithms in classification, regressing, recommender systems, clustering, deep learning.

·       Proficiency in autonomously conducting applied ML research with commercial applications.

·       Proficiency in Python, SQL, Pyspark.

·       Experience with cloud computing platforms such as Databricks, AWS, DataIku.

·       Experience with code versioning systems such as Github, Bitbucket, and experiment tracking systems like MLFLow.

·       Proficiency with computer science fundamentals in object-oriented design, data structures, and algorithmic design.

·       Experience communicating with business stakeholders.

·       Proficiency in English.

Preferred:

·       Experience with Recommender systems, Transformers, GNN

·       Familiarity with Deep Learning frameworks such as Pytorch, Keras, Tensorflow.

Expected base pay rates for the role will be between $85,000 and $135,000 per year at the commencement of employment. However, base pay if hired will be determined on an individualized basis and is only part of the total compensation package, which, depending on the position, may also include commission earnings, incentive compensation, discretionary bonuses, other short and long-term incentive packages, and other Morgan Stanley sponsored benefit programs.

Morgan Stanley's goal is to build and maintain a workforce that is diverse in experience and background but uniform in reflecting our standards of integrity and excellence. Consequently, our recruiting efforts reflect our desire to attract and retain the best and brightest from all talent pools. We want to be the first choice for prospective employees.

It is the policy of the Firm to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, creed, age, sex, sex stereotype, gender, gender identity or expression, transgender, sexual orientation, national origin, citizenship, disability, marital and civil partnership/union status, pregnancy, veteran or military service status, genetic information, or any other characteristic protected by law.

Morgan Stanley is an equal opportunity employer committed to diversifying its workforce (M/F/Disability/Vet).

Salary : $85,000 - $135,000