Applied AI ML Associate
Applied AI ML Associate
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Job Description
Join JPMorgan Corporate Investment Banks industry-leading data analytics team where youll combine cutting-edge machine learning techniques with unique data assets to optimize business decisions. As an Applied AI & Machine Learning Associate youll advance financial applications from business intelligence to predictive models and automated decision-making working closely with Digital & Platform Services Operations.
As an Applied AI ML Senior Associate in the Commercial & Investment Bank you will apply data analytics techniques from traditional statistics and machine learning to various datasets aiming to answer questions relevant to Operations. Collaborate with Digital & Platform Services Operations teams and other stakeholders to support the Corporate & Investment Bank and its partners.
Job Responsibilities:
- Research and develop innovative ML-based solutions to address Operations most challenging problems.
- Build robust Data Science capabilities scalable across multiple business use cases.
- Collaborate with the software engineering team to design and deploy Machine Learning services integrated with strategic systems.
- Research and analyze datasets using a variety of statistical and machine learning techniques.
- Communicate AI capabilities and results to both technical and non-technical audiences.
- Document approaches techniques and processes followed.
Required Qualifications Capabilities and Skills:
- Masters or PhD degree in a quantitative or computational discipline.
- Hands-on experience developing and deploying Data Science and ML capabilities in production at scale.
- Strong Python development and debugging skills.
- Ability to work both individually and collaboratively 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.
Preferred Qualifications Capabilities and Skills:
- Experience with Natural Language Processing (NLP).
- Ability to design intrinsic and extrinsic evaluations of a models performance aligned with business goals.
- Ability to work with non-specialists in a partnership model conveying information clearly and creating trust with stakeholders.
- Experience with machine learning frameworks (e.g. PyTorch TensorFlow) data science packages (e.g. Scikit-Learn NumPy SciPy Pandas statsmodels) and GenAI toolkit
- Experience in ML Ops
Required Experience:
IC
Employment Type
Full-Time
