Senior Quantitative Analytics Specialist
Wells Fargo · Hyderabad · onsite · Posted 57d ago
Undisclosed4–9 yrsfulltimeSourced from
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About this role
Job Summary
About this role: Wells Fargo is seeking a Senior Quantitative Analytics Specialist. Wells Fargo is seeking a hands-on experienced AI developer to contribute on projects related to development of Foundation models as well as Gen AI and Agentic applications supporting the bank across various lines of business.
Model, Methodology and Research (MMR) Team MMR is a specialized team which supports high priority research and development activities across Front line and second line teams within the bank. Team supports various strategic initiatives including development of Gen AI applications, in-house Large Language models, research for cutting-edge development in the industry, and Agentic development. Team also publish research papers in the top-tier conferences such as NeurIPS or ICLR.
In this role - 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
- 4+ years of Quantitative Analytics experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
- Bachelor''s degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science
- Masters or PhD in Computer Science, Machine Learning, Artificial Intelligence,Engineeringor related quantitative field
- 4+ years of experience in AI/ML model development
- 1+ year of experience building Foundation Models, Gen AI and Agentic AI applications
- Strong quantitative and analytical skills, with the ability to apply data analysis, modeling, visualization, statistics, research, and generative AI to generate insights, adapt quickly, and support innovative solutions.
- Ability to execute with urgency, apply data and software engineering skills to design, develop, and deliver scalable solutions, and drive operational excellence with strong data management and an enterprise mindset.
- Strong communication skills, with the ability to foster an inclusive environment and actively seek, apply, and respond to feedback in collaborative analytical settings.
- Strong business acumen with a commitment to providing excellent service and supporting data-informed business outcomes.
- Ability to act with integrity, support risk assessments, and apply risk controls to help manage risk in a disciplined, data-driven environment.
- Experience with pre-training, supervised fine-tuning (SFT) and post-training methodologies including RLHF, RLAIF, PPO, DPO, and GRPO
- Training and deploying models in cloud environments, including GCP
- Multi-agent architectures and orchestration frameworks likeLangChain,LangGraph, LangChain, LlamaIndex, Google's ADK,CrewAI
- Retrieval-Augmented Generation (RAG) applications and intelligent agent deployment
- Distributed GPU training
- Efficient model tuning approaches such asLoRAand PEFT
You will be hands-on working and contributing to the high-impact projects involving foundation models, large language models, multi-agent workflows, retrieval-augmented generation, human-in-the-loop AI, model evaluation, automation, and responsible AI deployment at enterprise scale.
- Design, pre-train, fine-tune, and evaluate transformer-based, foundation, and small language models (SLMs).
- Develop and deploy AI and machine learning solutions across generative AI, agentic systems, and traditional machine learning applications
- Design and build LLM-powered agents and multi-agent systems capable of planning, reasoning, task orchestration, and human-in-the-loop collaboration
- Monitor production models and AI systems, evaluating performance, stability, and model drift through testing and analytics frameworks
- Collaborate with cross-functional teams, technical experts, and business leaders across the organization
- Gain exposure to enterprise-scale AI development, governance, and risk management practices
- Apply AI, machine learning, and generative AI techniques to solve complex business problems.
- Build and optimize scalable model training and deployment pipelines.
- Leverage distributed computing and advanced training techniques to improve model performance and efficiency.
- Enhance model performance through distillation, quantization, and pruning.
- Optimize inference speed, latency, throughput, and cost for production AI systems.
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Skills
AutomationAI infrastructureanalytical thinkingai developmentCrewaiAi DeploymentAnalyticsDeploying ModelscloudCommunication SkillsData Managementdata analysiscomplianceCustomer RelationshipsArtificial Intelligence
About Wells Fargo
Wells Fargo
Financial Services
20k+
employees
1852
174 years old
Bengaluru/Bangalore, Karnataka
India
About
Wells Fargo works to create positive social impact in the communities it serves by supporting housing affordability, small business growth, financial health, and a low-carbon economy.
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Financial Services
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