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In office (Glasgow)
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Staff
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Sponsors visas in United States, Ireland; no register of this country names it

Confirmed on the employer's own hiring board on Nov 9, 2026. First seen by Alion on Nov 3, 2026. JPMorganChase scores A on the Alion truth index.

Overview
Company
Impact
Profile match
JPMorganChase is the largest bank in the United States by assets and one of the most systemically important financial institutions in the world, with a lineage running back through more than a thousand predecessor firms to the 1799 founding of the Bank of the Manhattan Company. It combines a dominant investment bank and markets business with Chase, the largest retail banking franchise in America, plus commercial banking and asset and wealth management. Headquartered in New York, the group is unusual among banks for the scale of its technology spending, running one of the largest engineering organisations of any financial institution and deploying its own internal AI platform across the firm.

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible.

As a Lead Data Scientist within Corporate Sector in Governance and Controls Technology (GCT), you will design and deliver trusted, market-leading products in a secure, stable, and scalable way. You will work across multiple technical areas and business functions, partnering with your team to deliver solutions that matter to our customers and the firm. You help strengthen our engineering culture through ownership, continuous improvement, and inclusive collaboration.

Job responsibilities

  • Collaborate with cross-functional teams to identify business requirements and develop data-driven solutions using AIML, Agentic/GenAI frameworks in a fast-paced environment.
  • Hands on experience in working on LLMs and agentic frameworks, such as Langchain/LangGraph and similar technologies.
  • Developing AI/ML and Gen AI/ Agentic AI solutions to address impactful business needs.
  • Hands on experience in all machine learning techniques, supervised, unsupervised, and semi-supervised techniques.
  • Strong experience in natural language processing (NLP) and its applications.
  • Solid coding level in Python programming language, with experience in leveraging available libraries, like Tensorflow, Keras, Pytorch, Scikit-learn, or others, to dedicated projects.
  • Working with other team members to productionize end-to-end AI/ML solutions.
  • Engaging in research and development of innovative relevant solutions.
  • Coaching and mentoring other AI/ML team members towards both personal and professional success
  • Collaborating with other teams across the firm to attain the mission and vision of the team and the firm. Engaging with stakeholders and understanding business requirements.
  • Act as a self-starter, independently taking initiative in driving assignments to completion and solving problems without escalation.

Required qualifications, capabilities, and skills

  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
  • Practical cloud native experience
  • Advanced degree in Computer Science, Data Science, Mathematics, or a related field.
  • Applied experience in data science, machine learning, or related areas.
  • Strong programming skills in Python with experience in PySpark, Spark SQL, and manipulating data.
  • Experience LLM Orchestration and Agentic AI libraries
  • Proficiency in using GenAI models (OpenAI or similar) to solve business problems.
  • Experience in building AI Agents, Agentic frameworks.
  • Experience in building and managing data lakes and data processing workflows using Databricks.
  • Ability to leverage AI agents and tools, such as Co-Pilot, to enhance productivity and code quality.
  • Excellent problem-solving skills and the ability to communicate ideas and results clearly to stakeholders.
  • Strong troubleshooting and problem-solving skills.
  • Fast learner with the ability to quickly develop Proof of Concepts and advance them to production.

Preferred qualifications, capabilities, and skills

  • Understanding of AWS component.
  • Experience integrating AI/ML models into data pipelines is a plus.
  • Experience with version control (Git) and CI/CD pipelines.
  • Financial service background
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