Senior Quantitative Analytics Specialist; Senior GenAI Data Scientist

Senior Quantitative Analytics Specialists (Senior GenAI Data Scientists)

Wells Fargo is seeking two Senior Quantitative Analytics Specialists (Senior GenAI Data Scientists) to support driving natural language processing (NLP) and large language model (LLM) initiatives as part of the Consumer Model Development group. This role is ideal for a seasoned professional passionate about building scalable Natural Language Processing (NLP) solutions and driving innovation in large language model (LLM) applications.

In this role, you will:

• Apply advanced statistical theory to quantify, analyze, and manage data, financial risks, and market dynamics through robust modeling approaches
• Collaborate and partner with internal and external stakeholders to gather requirements and deliver impactful, data driven and AI enabled solutions
• Engage with Audit, Model, Product, and technical stakeholders to ensure transparency, governance, and compliance with regulatory expectations
• Establish and promote best practices across the model lifecycle, including development, evaluation, validation, deployment, and monitoring, while contributing to analytical strategies, modeling approaches, and forecasting methodologies through execution of complex model development and implementation
• Drive innovation through proof-of-concept initiatives, experimentation, and applied research, while staying current on emerging trends in Generative AI, large language models (LLMs), and Natural Language Processing (NLP), and translating insights into practical business applications
• Guide and mentor junior team members, fostering technical excellence, collaboration, and knowledge sharing
• Lead the design, architecture, and implementation of scalable artificial intelligence (AI), machine learning (ML), Natural Language Processing (NLP), and large language model (LLM) solutions using advanced techniques, modern frameworks, and cloud native tools to support complex language understanding use cases

Posting Location(s):
Preferred locations listed below;
Relocation assistance is not available for this position.

• 333 Market Street, San Francisco, California
• 11625 N. Community House Road, North Carolina
• 401 S. Tryon Street, Charlotte, North Carolina

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 discipline such as mathematics, statistics, engineering, physics, economics, or computer science

Desired

Qualifications:

• Advanced analytical and strategic thinking skills with the ability to assess complex data, systems, architectures, and data flows to identify risks and opportunities and drive timely, data driven decision making
• Demonstrated ability to work independently, take initiative, and exercise sound judgment within a matrixed environment to drive business outcomes
• Advanced collaboration, influencing, and communication skills with the ability to build trusted relationships, align stakeholders, and communicate complex information effectively across all organizational levels, including executive leadership
• Demonstrated expertise in artificial intelligence (AI), including Generative AI, large language models (LLMs), Natural Language Processing (NLP), prompt engineering, multimodal models, and retrieval augmented generation, with experience leading initiatives from concept through production
• Experience with Agile practices, product management principles, and modernization initiatives, including automation and cloud transformation, within financial services or other regulated environments
• Familiarity with regulatory and compliance considerations related to artificial intelligence (AI) model development, validation, and deployment within regulated environments
• Knowledge of model evaluation metrics, performance optimization techniques, and responsible artificial intelligence (AI) practices, including bias mitigation
• Proficiency in Python with experience using machine learning (ML) frameworks (such as PySpark, PyTorch, Tensor Flow), Natural Language Processing (NLP) libraries (such as…