At a Glance
- Tasks: Design AI workflows and apply advanced analytics to transform finance processes.
- Company: Join J.P. Morgan, a leader in financial services and innovation.
- Benefits: Competitive salary, career growth, and opportunities to work with cutting-edge technology.
- Other info: Collaborative environment with a focus on continuous learning and innovation.
- Why this job: Make a real impact in finance using your passion for machine learning and AI.
- Qualifications: Experience in NLP, ML, and strong analytical skills required.
The candidate must excel in working in a highly collaborative environment together with the business stakeholders, technologists, and control partners to deploy solutions into production. A strong passion for machine learning is essential, along with a commitment to continuous learning, research, and experimentation with new innovations in the field. Candidates should possess a solid understanding of modern NLP and/or financial knowledge, hands‑on implementation experience, strong analytical thinking, and a keen interest in applying advanced analytics to solve complex problems in finance and asset management.
Job Responsibilities
- Design and implement agentic AI workflows that automate and streamline complex business processes.
- Design and apply advanced techniques such as semantic search, retrieval‑augmented generation (RAG), named entity recognition (NER), prompt engineering, and personalization for content extraction, search, question answering, reasoning, and recommendation.
- Develop LLM, NLP, and ML solutions that address client requirements and drive business transformation.
- Work closely with partner teams—including Business, Technology, Product Management, Strategy, and Business Management—to deploy and scale developed models in production environments.
- Build comprehensive testing setups to evaluate model performance and ensure efficacy and reliability.
- Communicate results effectively to business stakeholders through written reports, visualizations, and presentations.
- Stay current with the latest research in LLM, agentic AI, ML, and data science, and proactively identify and leverage emerging techniques to drive ongoing enhancement.
Qualifications, Capabilities, and Skills
- Proven experience applying NLP, LLM, and ML techniques to solve high-impact business problems.
- Demonstrated intellectual curiosity and a passion for staying current with the latest advancements in AI, LLMs, agentic AI frameworks, and data science.
- Proficiency in programming languages such as Python and familiarity with machine learning libraries and frameworks.
- Excellent communication skills and ability to work collaboratively in a fast-paced, dynamic environment.
- Prior experience in financial services or asset management is desirable, along with a strong interest in applying AI to the financial domain.
Company
J.P. MORGAN
Level of experience (years)
Senior (5+ years of experience)
Asset Management, Data Scientist, Vice President, London/Glasgow employer: NLP PEOPLE
At JPMorganChase, we pride ourselves on being an exceptional employer, offering a vibrant work culture that fosters innovation and collaboration. As an Applied AI ML Lead in Payments, you will not only have the chance to make a significant impact on global finance but also benefit from extensive career growth opportunities and mentorship within a diverse team. Our commitment to excellence and continuous learning ensures that your unique perspective is valued, making this an ideal environment for those looking to push the boundaries of technology in a meaningful way.
StudySmarter Expert Advice🤫
We think this is how you could land Asset Management, Data Scientist, Vice President, London/Glasgow
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We think you need these skills to ace Asset Management, Data Scientist, Vice President, London/Glasgow
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Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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