Applied AI Lead VP - Cross Functional

JP Morgan

Location: Greater London

Job Type: Full time

Last updated

Perfection not required
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Responsibilities The Applied AI and Machine Learning team at JP Morgan Corporate Investment Bank combines cutting edge machine learning techniques with the company’s unique data assets to optimize the business decisions we make. In this role, you will be part of our industry-leading data analytics team, and advance the state-of-the-art in financial applications ranging from generating business intelligence to predictive models and automated decision making. Our work spans the Corporate Investment Banking, with exceptional opportunities in each. The team covers a wide array of activities whether internally or externally focused: Finance functions, Controls, Legal, Operations, Digital Investment Banking and the Economic Research department.

  • Develop scalable tools leveraging machine learning models to solve real-world problems in areas such as Time Series predictions or Natural Language Processing. The ability to develop deep learning models will be seen as a useful addition.
  • Collaborate with all of JPMorgan's lines of business and functions in the Corporate Investment Bank: Markets, Global Investment Banking, Corporate Banking, Technology and Operations.
  • Lead your own project. Suggest, collect and synthesize requirements. Create an effective roadmap towards the deployment of a production-level machine learning application.

Required Skills:

  • Master’s or PhD in a quantitative field (e.g. statistics, mathematics, computer science, engineering, quantitative social, biological, or physical science) is strongly preferred.
  • Experience with Natural Language Processing, deep learning, experimental design and A/B testing, recommender systems or other deployed data products.
  • 5+ years of relevant analytics experience.
  • Excellent Python and SQL programming skills; familiarity with standard data science tooling; understanding of algorithms and software engineering fundamentals.
  • Ability to interpret business stakeholder requests and translate business problems into solvable data science problems, choose and correctly utilize appropriate methodology.
  • Analytics and ML/AI: skills to correctly interpret data; familiarity with ML/AI algorithms and open-source libraries.
  • Track record of speedily and rigorously developing and deploying user-facing machine learning models to resolve industry problems.
  • Superior communication and data visualization skills, such as the ability to choose appropriate medium of communication and visualization designs to represent findings.
  • Ability to build trust and reach agreement with stakeholders.
  • Personality profile: assertive, resourceful, inventive, persevering.
  • Experience working in software development and adept at using the command line or Linux.
  • Experience working with Big Data technologies such as Hadoop, Spark and Impala.
  • Experience with sophisticated statistical or econometrical models.
You’ve got this!