What are the responsibilities and job description for the Applied AI ML, Senior Associate - Sales Science position at JPMorgan Chase?
Join our Sales Science Data and Analytics team and help us optimize client engagement through our Consumer & Community Banking field employees and tools!
As a Quant Analytics Senior Associate in our Sales Science Data and Analytics team, you will help us optimize client engagement through our innovative projects and you will help us drive the future of field AI Technologies, leveraging ML tools and algorithms to deliver the right solutions as we reinvent CRMs and client/employee interactions at the firm. You will be part of an innovative team, working closely with business partners, product owners, and fellow data scientists to build new AI/ML solutions and productionlize them. You are someone with a passion for data, ML, and programming, who can build ML solutions at-scale with a hands-on approach with detailed technical acumen.
Job responsibilities
- Serve as a subject matter expert on a wide range of ML techniques and optimizations.
- Build and enhance ML workflows through advanced proficiency in large language models (LLMs) and related techniques.
- Conducting experiments using latest ML technologies, analyzing results, tuning models.
- Actively engage in hands-on coding to convert experimental results into robust production solutions.
- Take full ownership of the entire code development lifecycle in Python, from proof of concept and experimentation to delivering production-ready solutions.
- Integrate Generative AI within the ML Platform using state-of-the-art techniques.
Required qualifications, capabilities, and skills
- Bachelor's degree in Computer Science, Machine Learning, or a related field with 3 years of applied machine learning experience.
- 3 years of experience in one of the programming languages like Python, R, Java, etc. Intermediate Python is a must.
- Experience in applying data science, ML techniques and Reinforcement Learning to solve business problems.
- Solid background in Natural Language Processing (NLP) and Large Language Models (LLMs)
- Experience with machine learning and deep learning methods.
- Deep understanding and expertise in deep learning frameworks such as PyTorch or TensorFlow
- Ability to work on tasks and projects through to completion with limited supervision.
- Passion for detail and follow through. Excellent communication skills and team player.
Preferred qualifications, capabilities, and skills
- In-depth understanding of Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies.
- MS and/or PhD in Computer Science, Machine Learning, or a related field, with at least 4 years of applied machine learning experience preferred.
- Advanced knowledge in Reinforcement Learning or Meta Learning.
- Software development experience is a plus.
- Demonstrated ability to translate LLM pipelines/workflows into something less technical business partners can understand.
- Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods.
- Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc.