Job Description

JOB DESCRIPTION

We are HR Data and Analytics, a centralized global team responsible for all aspects of workforce data strategy, analytics and reporting, data governance, and the development of artificial intelligence and machine learning (AI/ML) based solutions. We have a vision to help make individuals, teams, and businesses at JPMC among the most engaged and productive in the world. Our mission is to create workforce insights that allow leaders to make evidence-based people decisions that help drive measurable business outcomes.


As an Applied AI/ML Senior Associate within our dynamic team, you will apply your quantitative, data science, and analytical skills to complex problems. You will collaborate with various teams to design and develop data science solutions, maintaining a deep understanding of the business problem. Your responsibilities will include data wrangling, data analysis, and modeling. You will advise on optimal solutions and provide insights on challenger models. You will be involved in strategic projects across the firm, making a significant impact at a leading financial services firm. Your role will be pivotal in developing data-centric solutions that enhance the firm's bottom line.

Job responsibilities

• Engaging with stakeholders and understanding business requirements
• Developing AI/ML solutions to address impactful business needs
• Working with other team members to productionize end-to-end AI/ML solutions
• Engaging in research and development of innovative relevant solutions
• Documenting developed AI/ML models to stakeholders
• Coaching other AI/ML team members towards both personal and professional success
• Collaborating with other teams across the firm to attain the mission and vision of the team and the firm

Required qualifications, capabilities, and skills

• Advanced degree in analytical field (e.g., Data Science, Computer Science, Engineering, Applied Mathematics, Statistics, Data Analysis, Operations Research)
• Experience in the application of AI/ML to a relevant field
• Demonstrated practical experience in machine learning techniques, supervised, unsupervised, and semi-supervised
• Strong experience in natural language processing (NLP) and its applications
• Solid coding level in Python programming language, with experience in leveraging available libraries, like Tensorflow, Keras, Pytorch, Scikit-learn, or others, to dedicated projects
• Previous experience in working on Spark, Hive, and SQL

Preferred qualifications, capabilities, and skills

• Financial service background
• PhD in one of the above disciplines


ABOUT US



J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.


We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.





ABOUT THE TEAM



Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.