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JPMorgan Chase is one of the world's oldest and largest financial institutions, known for its innovative spirit. The Applied AI/ML Associate role focuses on developing and deploying machine learning applications and models, collaborating with team members to create scalable solutions in the Payments space.
Responsibilities
- Actively work to gain a deep understanding of intricate business challenges and processes, and identify opportunities for AI and ML solutions.
- Develop innovative ML-based solutions to address Operations' most challenging problems.
- Collaborate with business partners to drive data-led transformations of the businesses.
- 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.
Qualification
Required
- Bachelor’s or Master’s degree in a quantitative field (e.g., Data Science, Computer Science, Applied Mathematics, Statistics, Econometrics).
- 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.
- Excellent solution ideation, problem solving, communication (verbal and written), and teamwork skills.
Preferred
- Experience with Natural Language Processing (NLP).
- Ability to design intrinsic and extrinsic evaluations of a model's performance aligned with business goals.
- Experience with machine learning frameworks (e.g., PyTorch, TensorFlow), data science packages (e.g., Scikit-Learn, NumPy, SciPy, Pandas, statsmodels) and GenAI toolkit.
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