What are the responsibilities and job description for the Chase Modeling - Applied AI ML Senior Associate position at JPMorgan Chase?
Join a team that consists of an intellectually diverse team of economists, statisticians, engineers, and other analytics professionals, focused on applied AI and quantitative modeling.
As an Applied AI ML Senior Associate, within the Consumer Business Modeling team you will utilize cutting edge quantitative and computational techniques and leverage one of the world’s largest repositories of consumer data.
Job Responsibilities:
- Apply critical thinking skills and perform advanced analytics with the goal of solving complex and multi-faceted business problems.
- Generate deep insights through the analysis of data and understanding of business processes and turn them into actionable recommendations.
- Contribute to the full modeling lifecycle, including defining the objective and key decision variables, choosing appropriate methodologies, performing advanced quantitative and statistical analysis of large datasets, and communicating results.
- Develop presentations to summarize and communicate key messages to senior management, sponsors and colleagues.
- Become a subject matter expert and trusted advisor in the statistical, optimization and/or machine learning modeling discipline.
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Actively contribute to the continuous learning mindset of the organization by bringing in new ideas and perspectives that stretch the thinking of the group.
Required Qualifications, Capabilities, and Skills:
- Advanced degree in Statistics, Data Science, Engineering, Computer Science, Economics, Operations Research, Mathematics, or equivalent quantitative field. Ph.D. is a plus.
- Outstanding written and oral communication skills to present analytical findings and exercise influence among key project stakeholders.
- Experience in developing machine learning, optimization, and/or statistical models to solve real world problems (e.g. Classification, Regression, Recommender Systems, Natural Language Processing, or Neural Language Modeling).
- Proficiency in at least one programming language is required, with Python preferred.
- Strong analytical, interpretive, and problem-solving skills, with demonstrated ability of thinking outside the box.
- Significant experience working with very large scale (structured and unstructured) data.
Preferred Qualifications, Capabilities, and Skills:
- Familiarity with big-data environments (e.g. Hadoop, Spark).
- Model development experience on a cloud development platform.
- Banking & Financial Services background or experience.