Senior Quantitative Analytics Specialist - AI and ML Audit

Key Skills

Apache Hadoop, C Programming, C++, Data science techniques, Java Programming, Machine learning techniques, MapReduce, Python Programming, PyTorch, R Programming, Scala Programming, SQL, TensorFlow

Job Description

Wells Fargo is seeking a Senior Quantitative Analytics Specialist within its Artificial Intelligence (AI) Machine Learning (ML) Center of Excellence group.

The AI and ML CoE team in Enterprise Analytics and Data Science (EADS) is responsible for developing and deploying NLP, machine learning, and AI solutions for key strategic Enterprise initiatives such as customer experience improvement, risk management and compliance, business operational excellence, and team member experience. The team is looking for an experienced analytics professional to add to its AI/ML/NLP model development team for Internal Audit.

As part of the AI/ML/NLP data science team for Internal Audit model development, you will be responsible for designing, developing, and implementing AI/ML models focusing on Internal Audit initiatives for the enterprise and Wells Fargo lines of business. You will be leveraging unstructured text such as emails, text messages, notes, and semi-structured data in combination of structured data to apply text analytics and AI/NLP/ML techniques. You will use open stack programming languages (primarily Python) and/or vendor solutions to develop models and deploy them on Wells Fargo’s AI platform. The ideal candidate should be able to think outside the box to uncover new ways to analyze unstructured data in conjunction with analytical tools to answer complicated business questions. As part of the model development team, you will be responsible of delivering solutions that meet business needs as well as any efforts related to model documentation and reviews to ensure the modeling processes and procedures meet corporate model risk policies and requirements.

In this role, you will:

• Partner with Internal Audit executives and senior leaders to frame the problem and define/identify business objectives
• Design, develop, and deploy AI/ML models using state of the art NLP and ML techniques available in the open stack and/or vendor solutions
• Data visualization
• Communicating the results
• Responsible of model development document and monitoring processes
• Adhere to corporate model risk policy and ensure compliance with model risk management
• Working with other data science teams to identify, gather, retain, and publicize modeling artifacts required for approved and repeatable processes
• Contribute to NLP data science teams group effort to stay concurrent with the cutting edge and bleeding edge of NLP/ML/DL algorithms, methodologies in the open source community and vendor solutions.
• Work with AI technology and production teams to operationalize models

In this role, you will also:

• Perform highly complex activities related to creation, implementation and documentation
• Use highly complex statistical theory to quantify, analyze and manage markets
• Forecast losses and compute capital requirements providing insights, regarding a wide array of business initiatives
• Utilize structured securities and provide expertise on theory and mathematics behind the data
• Manage market, credit, and operational risks to forecast losses and compute capital requirements
• Participate in the discussion related to analytical strategies, modeling and forecasting methods
• Identify structure to influence global assessments, inclusive of technical, audit and market perspectives
• Collaborate and consult with regulators, auditors and individuals that are technically oriented and have excellent communication skills

Required Qualifications:

• 4+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
• Master's degree or higher in a quantitative field such as mathematics, statistics, engineering, physics, economics, or computer science
• 2+ years of experience with machine learning model development
• 2+ years of Python experience
• 2+ years of SQL experience
• 1+ years of Natural Language Processing (NLP) experience

Desired Qualifications:

• Big Data experience
• Meeting facilitation experience in leading discussions that result in consensus and commitment
• Ability to work and influence successfully within a matrix environment and build effective business partnerships with all levels of team members
• Good analytical skills with high attention to detail and accuracy
• GitHub experience
• Experience with search engine libraries, such as, but not limited to Stanford NLP Library or Lucene search engine