To promote opportunities here… there are positions now for AI/ML/NLP researchers. Please message me if you are interested! Happy to refer!
Just a quick extra note…: Wells Fargo is a traditional company so I guess thats why the “official” job description (below) can sound “traditional” (unfortunately ). But the hiring manager is open, he’s an engineer himself. The gist of this job is research and implementing papers (and/or write your own - but not required if you are just interested in coding is fine). The team is pretty free style, like a lab. So please dont mind some “stubborn” requirements on graduate schools.
Apologize, here’s more info:
company: Wells Fargo
location: Charlotte (preferred), San Francisco, some other US locations (probably negotiable)
Job ID: 5458818
Job description (this is the official version):
Wells Fargo’s Corporate Model Risk (CMoR) organization is seeking highly qualified quantitative associates (QA) to join its Advanced Technologies for Modeling (AToM) Group. The responsibilities of the AToM group is to advance the Bank’s state-of-the-art practices in the areas of credit, operational, and market risk management.
The individuals will be involved in the development of cutting edge models, methods and algorithms in machine learning (ML), advanced statistics, natural language processing (NLP), and other dimensions of artificial intelligence (AI), with the goal of driving best modeling practice across the bank. Specific duties include, but are not limited to, the following:
Identify state-of-the-art techniques in the literature on ML, NLP, and advanced statistics and adapting them for applications in risk management;
Drive new methodology development by conducting applied research in the above areas for current and emerging applications in risk modeling;
Disseminate best practice across the quantitative modeling community within the bank through technology transfer, white papers, and seminars;
Design, implement and automate model replication, benchmarking and testing with CMoR’s advanced computing platform to improve effectiveness and efficiency;
Collaborate with internal and external quantitative communities including academic community to keep abreast with the latest developments and practices in quantitative risk.
Master’s degree or higher in a quantitative field such as computer science, statistics, mathematics, physics, or engineering, upon start date of the program.
A PhD in Computer Science, Statistics, Electrical Engineering, or a related quantitative discipline with emphasis on Machine Learning and AI.
Excellent verbal, written, and interpersonal communication skills.
Other Desired Qualifications
In-depth knowledge of ML and AI methodologies such as ensemble algorithms, neural networks, and natural language processing;
In-depth knowledge of some of the following computation fields: data structures, algorithms, database technologies, distributed computing, and GPU computing;
Excellent background in advanced statistical concepts, modeling, and data analysis techniques;
Strong computing and programming background and knowledge of one or more languages such as Python, Java and R;
Experience with ML/AI computing platforms and tools such as TensorFlow and Keras;
Ability to work with large datasets and some experience with database management, data retrieval, and tools such as Hadoop, Spark and SQL;
Excellent writing and communications for model documentation and presentations to audiences of all technical backgrounds;
Strong conceptual and quantitative problem solving skills and demonstrated ability to think independently;
Capable of working on cross-organizational projects and collaboratively partnering with other activities; and
A “can-do” personal style/attitude and the ability to work collaboratively with various activities will be a key success in this role.