What are the responsibilities and job description for the Applied AI ML Senior Associate position at JPMorgan Chase?
At JPMorgan, we are not looking for job seekers. We seek change makers who want to make an impact.
As an AI ML Sr. Associate within our dynamic team, you will be responsible for promoting long-term profitable growth by leveraging your strong business acumen. You will also collaborate effectively within a team environment and communicate results to senior management in a clear and concise manner.
you will drive long term profitable growth with strong business acumen, collaborate in a team environment, and effectively communicate results to senior management.
Job Responsibilities -
- Design and develop machine learning models to drive impactful decisions for the card business throughout the customer lifecycle (e.g., acquisition, account management, transaction authorization, collection).
- Research, develop, document, implement, maintain, and support tools and frameworks for AI/ML model explainability and fairness.
- Utilize cutting-edge machine learning approaches and construct sophisticated machine learning models including deep learning architectures on big data platforms.
- Work closely with the senior management team to develop ambitious, innovative modeling solutions and deliver them into production.
- Collaborate with various partners in marketing, risk, technology, model governance, research etc. throughout the entire modeling lifecycle (development, review, deployment, and use of the models)
Required qualification, capabilities and skills-
- Ph.D. or Master’s degree from an accredited university in a quantitative field such as Computer Science, Mathematics, Statistics, Econometrics, or Engineering
- Demonstrated experience in designing, building, and deploying production quality machine learning models.
- Deep understanding of advanced machine learning algorithms (e.g., regressions, XGBoost, Deep Neural Network – CNN and RNN, Clustering, Recommendation) as well as design and tuning.
- Experience in interpreting machine learning models such as XGBoost, GBM, etc.
- At least one year of experience and proficiency in coding (e.g., Python, Tensorflow, Spark, or Scala) and big data technologies (e.g., Hadoop, Teradata, AWS cloud, Hive) .
- Experience in credit card industry with strong business acumen.
- Strong ownership and execution; proven experience in implementing models in production
Preferred qualification, capabilities and skills-
- Demonstrated expertise in data wrangling and model building on a distributed Spark computation environment (with stability, scalability and efficiency). GPU experience is desired.
- Experience in interpreting deep learning models is a plus.
