Lead Quantitative Analytics Specialist – AI and Machine Learning
Wells Fargo
full-time
Posted on:
Location Type: Hybrid
Location: San Francisco • California, North Carolina • 🇺🇸 United States
Visit company websiteSalary
💰 $191,000 - $305,000 per year
Job Level
Senior
Tech Stack
AzureCloudGoogle Cloud PlatformPython
About the role
- Lead the design, development, and implementation of NLP and LLM-based systems for complex language understanding tasks.
- Architect scalable and robust solutions using state-of-the-art NLP techniques and open-source or vendor frameworks.
- Guide and mentor junior team members, fostering technical excellence and collaboration.
- Partner with cross-functional teams to gather requirements and deliver impactful AI-driven solutions.
- Engage with regulators, auditors, and technical stakeholders to ensure transparency and compliance.
- Stay abreast of emerging trends in NLP, LLMs, and GenAI, and translate research into practical applications.
- Drive innovation through proof-of-concept initiatives and exploratory research.
- Establish and promote best practices for model development, evaluation, and deployment.
- Build and operationalize AI/ML models using modern NLP libraries and cloud-native tools.
Requirements
- 5+ 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
- Hands-on experience with GenAI frameworks and tools
- Deep understanding of ML, LLMs, and GenAI technologies
- Strong strategic, communication, and collaboration skills
- Experience in responsible AI practices and regulatory alignment
- Strong programming skills in Python and experience with NLP libraries (NLTK, spaCy, Hugging Face)
- Strong experience in developing NLP models like logistic regression, XGboost, LightGBM’s linear SVC etc.
- Demonstrated experience fine-tuning and deploying LLMs (GPT, BERT, T5, etc.)
- Experience with prompt engineering and optimization techniques
- Knowledge of model evaluation metrics and performance optimization
- Experience leading technical teams and managing complex projects
- Experience with multimodal models and retrieval-augmented generation
- Contributions to open-source NLP/LLM projects or research publications
- Experience with MLOps and model deployment pipelines
- Knowledge of responsible AI practices and bias mitigation techniques
- Experience with cloud platforms (GCP, Azure) for ML workloads
- Background in specific domain applications (healthcare, finance, legal, etc.)
- Experience with distributed computing for large-scale model training
Benefits
- 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
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
NLPLLMGenAIPythonNLP librarieslogistic regressionXGboostLightGBMGPTBERT
Soft skills
strategic skillscommunication skillscollaboration skillsmentoringtechnical excellence
Certifications
Master's degreequantitative discipline