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About this role: Wells Fargo is seeking talent to join the 2027 Quantitative Analytics Summer Internship Program ACI (PhD). Learn more about the career areas and lines of business at wellsfargojobs.com
Program Overview | The Wells Fargo Quantitative Analytics Internship Program offers PhD candidates an opportunity to apply advanced analytics, artificial intelligence, and machine learning to complex business challenges at one of the world's leading financial institutions.
This 10-week summer internship combines hands-on project experience, mentorship, technical training, and exposure to senior leaders. Through this 10-week internship you'll work alongside experienced quantitative professionals, helping develop and evaluate innovative solutions that support business strategy, risk management, and customer experience across Wells Fargo.
You'll be expected to bring fresh perspectives, explore innovative approaches, and contribute to solutions that support Wells Fargo's strategic priorities. Along the way, you'll develop not only your technical capabilities but also the business acumen and leadership skills needed to succeed in a highly collaborative environment.
Whether you're advancing cutting-edge AI research, developing innovative analytical solutions, or collaborating with teams across the organization, you'll have opportunities to make an impact while continuing to grow professionally. This internship offers valuable experience, mentorship, and networking opportunities that can help prepare you for the next step in your career. High performing interns may receive consideration for full-time roles after graduation. #earlycareers
You could work on high-impact projects like:
Develop AI-powered advisors and decision support systems that synthesize customer, relationship, market, and enterprise data to generate insights, recommendations, and actions.
Build Generative AI assistants and intelligent agents that leverage enterprise knowledge, reasoning, and workflow orchestration to support employees and customers.
Design and deploy agentic AI and multi-agent systems that automate customer service, operational, and business processes through planning, task execution, and human-in-the-loop collaboration.
Create enterprise knowledge intelligence platforms using Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), multimodal AI, and structured and unstructured data to power search, reasoning, decision support, and workflow automation.
Advance the state of enterprise AI through model training, evaluation, optimization, and deployment of LLMs, speech technologies, and emerging foundation models.
Deploy scalable Generative AI and machine learning solutions that improve productivity, customer experience, risk management, decision-making, and operational efficiency across the enterprise.
Applying statistical and quantitative techniques to validate model design, calibration, and implementation.
What You’ll Experience:
Spend your Intern Induction Week at an offsite location
Structured and engaging onboarding experience
Speaker series with Wells Fargo senior leaders
Professional development opportunities
Networking and engaging with peers
On-the-job experiences contributing to strategic business goals
Program dates: June – August 2027
Program Duration: 10 weeks
Program Location: Charlotte, NC
Required Qualifications:
2+ years of work experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Required Qualifications for Europe, Middle East & Africa only:
Work experience, or equivalent demonstrated through one or a combination of the following: work experience, training, education
Desired Qualifications:
Currently pursuing a PhD degree in Computer Science, Statistics, Data Science, Econometrics, Mathematics, Engineering or related quantitative field, with an expected graduation date after December 2027.
Technical Skills
Strong programming experience with tools such as Python, Go, C++, Rust, Java, Spark, or similar technologies
Hands-on experience developing machine learning and AI solutions in research, academic, or industry environments
Knowledge and Experience In:
Large Language Models & Model Training
Experience with supervised fine-tuning (SFT) and post-training methodologies including RLHF, RLAIF, PPO, DPO, and GRPO
Training and deploying models in cloud environments, including GCP
Agentic AI
Multi-agent architectures and orchestration frameworks like LangChain, LangGraph, Google's ADK, CrewAI
Retrieval-Augmented Generation (RAG) applications and intelligent agent deployment
AI Infrastructure & Optimization
Distributed GPU training
Efficient model tuning approaches such as LoRA and PEFT
Additional Qualifications
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 communicat
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