CIB - Applied AI & Machine Learning Associate CIB - Applied AI & Machine Learning Associate …

J.P.Morgan
in New York, NY, United States
Permanent, Full time
Be the first to apply
Competitive
J.P.Morgan
in New York, NY, United States
Permanent, Full time
Be the first to apply
Competitive
CIB - Applied AI & Machine Learning Associate
About J.P. Morgan Corporate & Investment Bank

J.P. Morgan's Corporate & Investment Bank (CIB) is a global leader in Banking. The world's corporations, governments and institutions entrust us with their business in more than 100 countries. The Corporate & Investment Bank supports our clients around the world providing strategic advice, raising capital and managing risk.

The Applied AI and Machine Learning team at JPMorgan 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.

The successful candidate will apply data analytic from traditional statistics to complex machine learning techniques for a wide-ranging set of banking applications such as -but not limited to- risk assessment, anti-money laundering detection, bond issuance pricing models, client data remediation, fund activism and client relationship management. Machine learning techniques will include familiarity or knowledge of at least one of the following areas: time series analysis, supervised learning, pattern detection, natural language, maximum entropy models and neural networks.

The team benefits from the support of separate Data Engineering and Tech deployment teams to help bring projects to production swiftly.

Responsibilities
  • 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.


  • Excellent Pythonand SQL programming skills; familiarity with standard data science tooling;understanding of algorithms and software engineering fundamentals.
  • Ability tointerpret business stakeholder requests and translate business problems intosolvable data science problems, choose and correctly utilize appropriatemethodology.
  • Analytics andML/AI: skills to correctly interpret data; familiarity with ML/AI algorithmsand open-source libraries.
  • Track record ofspeedily and rigorously developing and deploying user-facing machine learningmodels to resolve industry problems.
  • Superiorcommunication and data visualization skills, such as the ability to choose appropriatemedium of communication and visualization designs to represent findings.
  • Ability to buildtrust and reach agreement with stakeholders.
  • Personalityprofile: assertive, resourceful, inventive, persevering.


Bonus Skills:
  • Master's or PhDin a quantitative field (e.g. statistics, mathematics, computer science,engineering, quantitative social, biological, or physical science) is stronglypreferred.
  • Experience withNatural Language Processing, deep learning, experimental design and A/B testing,recommender systems or other deployed data products.
  • Experienceworking in software development and adept at using the command line orLinux.
  • Experienceworking with Big Data technologies such as Hadoop, Spark and Impala.
  • Experience withsophisticated statistical or econometrical models.
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