Applied AI / ML Lead - Vice President - AI for Digital & Platform Services Operations

JP Morgan

Location: Greater London

Job Type: Full time

Posted


About Data Analytics within Corporate & Investment Bank

Data Analytics at J.P. Morgan Corporate Investment Bank combines cutting edge machine learning techniques with the company’s unique data assets to optimize all 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.

The role will be in the firm’s Applied AI and Machine Learning organization and will involve working closely with Digital & Platform Services Operations.

The successful candidate will apply data analytics techniques from both traditional statistics and machine learning to a combination of third party, publicly available and J.P. Morgan proprietary datasets, with the goal of answering questions relevant to Operations.

About Operations

The Digital & Platform Services Operations teams support the Corporate & Investment Bank and its partners and functions including Technology, Data Science, Client Service, Product and Platform as well as other businesses and stakeholders across the firm.

Responsibilities

  • Research and develop innovative ML based solutions to some of Operations’ hardest problems.
  • Understand the Operations business to formulate relevant high impact business questions that can be answered through data analysis.
  • Build robust Data Science capabilities which can be scalable across multiple business use cases.
  • Collaborate with Tech partners to design and deploy Machine Learning services that can be integrated with strategic systems.
  • Think strategically to leverage reusable components within the firm and state of the art available externally when building the capabilities.
  • Research and analyze data sets using a variety of statistical and machine learning techniques.
  • Communicate results to technical and non-technical audiences and provide appropriate context.
  • Document approaches and techniques used.

Required Technical Qualifications and experience

  • Significant experience in a reputable work environment.
  • A Bachelor's, Master's or PhD in a quantitative or computational discipline.
  • Experience with Natural Language Processing (NLP).
  • Significant hands-on experience developing and deploying Data Science and ML capabilities in production at scale.
  • Strong ability to develop and debug in Python
  • Ability to work both individually and collaboratively in teams, in order to achieve project goals.
  • Being curious, hardworking, detail-oriented, and motivated by complex analytical problems.
  • Being results and client focused and follow the agile development paradigm.

Nice to Have

  • Ability to design or evaluate intrinsic and extrinsic metrics of model performance in alignment with business goals.
  • Ability to independently research and propose alternatives with some guidance as to problem relevance.
  • Ability to work with non-specialists in a partnership model, conveys information clearly and creates a sense of trust with stakeholders.
  • Strong experience with machine learning APIs and computational packages (examples: Scikit-Learn, NumPy, SciPy, Pandas etc).
  • Experience with neural network packages (e.g. PyTorch, TensorFlow etc).
  • Experience with big data technologies such as Spark and Hadoop.
You’ve got this!