Quantitative Analytics Specialist

Key Skills

Apache Hadoop, C++, Java Programming, Keras software library, Python Programming, R Programming, SAS, SQL, TensorFlow

Job Description

Wells Fargo is seeking a Quantitative Analytics Specialist...to join its Advanced Technologies for Modeling (AToM) Group in the Corporate Model Risk (CMoR) organization. The responsibilities of the AToM group include development of cutting-edge models, algorithms, visualization tools, and computing environment to advance the Bank’s practices in the areas of credit, operational, and market risk management. 

In this role, you will:

• Be involved in the development of state-of-the-art methods in statistical modeling, machine learning (ML), and implementing them in efficient/scalable algorithms.
• Depending on the skills and interests of the candidate, they will work initially on structured (tabular) data or unstructured (text and conversational) data. Specific duties include, but are not limited to, the following:
• Identify state-of-the-art techniques in modeling (Statistics, ML, and Deep Learning or DL) as well as implementing them for applications in risk management.

• Drive the development of methodology and algorithms by conducting applied research.
• Disseminate best practice across the quantitative modeling community within the bank.
• Develop model library to support validation process.
• Design benchmark models as well as implementing and automating their use within our advanced computing platform; and
• Collaborate with internal and external quantitative communities to keep abreast of latest developments and practices in quantitative risk.

• Develop, implement, and calibrate various analytical models
• Perform highly complex activities related to financial products, business analysis and modeling
• Perform basic statistical and mathematical models using Python, R, SAS, C++ and SQL
• Perform analytical support and provide insights regarding a wide array of business initiatives
• Provide solutions to business needs and analyze workflow processes to make recommendations for process improvement in risk management
• Collaborate and consult with peers, colleagues, managers, and regulators to resolve issues and achieve goals

Required Qualifications, US:

• Master s degree in the above areas with 2+ years of experience in one or a combination of the previously mentioned fields above

Desired Qualifications:

• A PhD in Computer Science, Statistics, Data Science, Machine Learning, Electrical Engineering, or a related quantitative discipline.
• Excellent background in modeling and coding.
• In-depth knowledge of ML/DL algorithms and their implementation.
• Strong computing and programming background and knowledge of one or more languages such as Python, Java and R.
• Some experience with ML/AI computing platforms and tools such as TensorFlow and Keras.
• Some experience with GPU programming, multi-core, or distributed programming.
• Ability to work with large datasets and some experience in database management and tools such as Hadoop, Spark and SQL.
• Ability to take initiative and work independently in a structured environment.
• Excellent writing and communication skills for documentation and presentations to audiences of all technical backgrounds.
• Strong conceptual and quantitative problem-solving skills and demonstrated ability to contribute independently; and
• Capable of working on cross-organizational projects and collaboratively partnering with other groups.