Lead Quantitative Analytics Specialist

About the Role

Key Responsibilities

• Drive end-to-end research projects in AI / Generative AI / Agentic AI / Machine Learning from ideation and experimentation to implementation and evaluation.
• Drive the exploration, application, and rigorous evaluation of emerging AI technologies that solve real-world challenges.
• Collaborate closely with interdisciplinary teams, including researchers, data scientists, applied engineers, and domain experts.
• Translate research insights into impactful business solutions, open-source contributions, patents, and publications.
• Contribute to the development of innovative AI systems that enhance Wells Fargo's products, services, and operations.
• Publish in top-tier AI/ML conferences and journals and represent Wells Fargo in the broader AI research community.

Requirements

• 5+ years of Quantitative Analytics experience, or equivalent demonstrated through work experience, training, military experience, or education.
• Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science.

Nice to Have

• PhD in Computer Science or related field or a MSc with at least 3 years of relevant industry or research experience.
• Proven research track record with publications in top-tier AI/ML conferences such as NeurIPS, ICML, ICLR, NAACL, or EMNLP.
• Deep expertise in Foundation Models, Large Language Models (LLMs), Large Reasoning Models, Multimodal Models, Agentic AI.
• Hands-on experience with AI/ML frameworks such as TensorFlow, PyTorch, Hugging Face, and AWS.
• Strong proficiency in rapid prototyping and structured software development practices.
• Experience with version control, code reviews, and scalable system design.
• Advanced programming skills in Python, with additional experience in Java or C++ considered a strong asset.
• Ability to write clean, efficient, and scalable code in production and research environments.
• Strong intellectual curiosity and enthusiasm for solving complex problems, especially in financial services.
• Interest in applying AI/ML to financial use cases such as risk modeling, fraud detection, or customer personalization.

Qualifications

• Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science.

Benefits & Perks

• Health benefits
• 401(k) Plan
• Paid time off
• Disability benefits
• Life insurance, critical illness insurance, and accident insurance
• Parental leave
• Critical caregiving leave
• Discounts and savings
• Commuter benefits
• Tuition reimbursement
• Scholarships for dependent children
• Adoption reimbursement