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JPMorgan Applied AI Associate - Markets Operations 
United Kingdom, England, London 
126915318

15.09.2024

About the role

As a member of the CIB Applied AI/ML for Operations team, you will have the unique opportunity to be a critical player in our firm-wide efforts to shape the future of banking. Crucial to this is helping to transform Operations teams, where you will have a direct impact on the behind-the-scenes management and functioning of the bank's corporate and investment banking services.

Finance background is not a must-have. If you get as excited about machine learning theory as you get about Python development, we’d love to speak with you.

In this role, you will:

  • Interact with very large datasets in the financial domain currently not available anywhere else
  • Write production-ready code and work with tech teams to ensure your machine learning solution is deployable at scale across multiple lines of business
  • Develop products that can change how corporate and investment banking is done today


Responsibilities

  • Research and develop innovative ML based solutions to some of Operations' hardest problems
  • Build robust Data Science capabilities which can be scalable across multiple business use cases
  • Collaborate with software engineering team to design and deploy Machine Learning services that can be integrated with strategic systems
  • Research and analyse data sets using a variety of statistical and machine learning techniques
  • Communicate AI capabilities and results to both technical and non-technical audiences
  • Document approaches taken, techniques used and processes followed

Required Technical Qualifications And Experience

  • Masters degree in a quantitative or computational discipline
  • Commercial experience developing and deploying Data Science and ML capabilities in production at scale
  • Strong Python development and debugging skills
  • Experience with Natural Language Processing (NLP)
  • Experience with machine learning frameworks (pytorch, tensorflow) and data science packages (examples: Scikit-Learn, NumPy, SciPy, Pandas, statsmodels)
  • Ability to to work both individually and in collaboration with others
  • Curiosity, attention to detail and interest in complex analytical problems
  • Results-driven mindset and client focus
  • Ability to work in agile cross-functional teams

Nice to Have

  • Ability to design intrinsic and extrinsic evaluations of a model's performance which are aligned with business goals
  • Ability to work with non-specialists in a partnership model, conveying information clearly and creates a sense of trust with stakeholders
  • Experience with inference, training and deployment of Large Language Models
  • Experience with big-data technologies such as Spark