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

JP Morgan

Location: Greater London

Job Type: Full time

Posted

The most difficult thing is the decision to act, the rest is merely tenacity.
- Amelia Earhart

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 Securities Services Operations and Markets Operations in Digital & Platform Services.

About Operations

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

Responsibilities

The successful candidate will apply data science 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 Digital & Platform Services Operations.

  • Collaborate with Operations colleagues to formulate relevant financial and business questions that can be answered by data analysis.
  • Research and analyze data sets using a variety of statistical and machine learning techniques
  • Communicate final results and give context.
  • Document approach and techniques used.
  • Work on longer term projects, building tooling that can be used to scale certain types of analyses across multiple datasets and business use cases.
  • Collaborate with other J.P. Morgan machine learning teams.

Required Technical Qualifications and experience

  • MS or PhD in a machine learning discipline, e.g. Computer Science, Mathematics, Statistics, Operations Research, Data Science, Economics, Engineering, Physics
  • Hands-on experience analyzing data
  • Strong ability to develop and debug in Python or similar professional programming language
  • Able to work with non-specialists in a partnership model, conveys information clearly and creates a sense of trust with stakeholders
  • Experience with machine learning APIs and computational packages (examples: TensorFlow, Theano, PyTorch, Keras, Scikit-Learn, NumPy, SciPy, Pandas, statsmodels)
  • Expertise with deep learning, tree-based ensembles and / or natural language processing (NLP)
  • Problem solving and collaboration skills

Nice to Have

  • Experience with big-data technologies such as Hadoop, Spark, SparkML, etc.
  • Experience with Unix and LaTeX
  • Should be able to work both individually and collaboratively in teams, in order to achieve project goals
  • Must be curious, hardworking and detail-oriented, and motivated by complex analytical problems
  • Must have the ability to design or evaluate intrinsic and extrinsic metrics of your model’s performance which are aligned with business goals
  • Must be able to independently research and propose alternatives with some guidance as to problem relevance
  • Must be able to undertake basic and advanced EDA, may require some direction from more senior team; should be aware of limitation and implication of methodology choices
  • Ensures re-use and sharing of ideas within team and locale
  • Able to work with non-specialists in a partnership model, conveys information clearly and creates a sense of trust with stakeholders
  • Shows institutional awareness and some understanding of applied problem solving, may require coaching and guidance as to how to most rapidly reach a satisfactory conclusion
You’ve got this!