Job Description

Join a team where your expertise in analytics and machine learning shapes the future of customer engagement. Experience a culture that values curiosity, collaboration, and growth.

As a Quant Analytics Senior Associate within Machine Learning Intelligent Operations team, you will play a key role in optimizing Conversational Insights and Insights for Coaching products. Your responsibilities will span the entire problem-solving lifecycle, including: identifying gaps through thorough and inquisitive analyses, conducting root cause analyses using causal inference and machine learning techniques, developing prototype analytics solutions, building and updating business cases, scoping analyses and developing hypotheses, gathering and analyzing complex data, quantifying business value generated through A/B tests or non-randomized pilot, generating actionable insights and delivering presentations to product teams.

Job Responsibilities

Conduct end-to-end data analysis to improve model performance and operational processes
Transform complex datasets and automate reporting for business driver analysis
Identify friction points across customer and specialist interaction channels
Collaborate with teams to integrate business assumptions and validate hypotheses
Present clear, actionable insights to peers, leadership, and business partners
Investigate and resolve issues in data collection, model development, and production
Develop and document SQL and Python codebases, data dictionaries, and model outputs
Support agile, digital, or scrum teams in new product development
Quantify business value generated through experiments and pilots
Generate and deliver presentations to product teams
Enable customer self-service across engagement channels

Required Qualifications, Capabilities, And Skills

Bachelor's degree in Economics, Data Analytics, Statistics, or a STEM field and 6 years of analytics experience; or Master's degree in these fields and 2 years of analytics experience
Hands-on experience with Excel PivotTables, PowerPoint, Tableau, Alteryx, and Python Jupyter Notebook
Solid programming skills in SQL
Strong writing and presentation abilities
Strong understanding of multi-linear regression, logistic regression, clustering, classification techniques including LightGBM and XGBoost, controlled experiments, and causal inference methods
Professional experience with AWS, Spark/EMR, ChatGPT, Confluence, and Snowflake
Proficient in big data ETL processes for structured and unstructured databases
Excellent communication skills for developing and delivering concise presentations
Detail-oriented problem solver with a track record of meeting tight deadlines
Collaborative team player with curiosity and ability to operate independently

Preferred Qualifications, Capabilities, And Skills

Extensive experience in consumer banking operations, servicing, collections, or marketing
Trained in multivariate statistics, regression analysis, Python, SQL, and visualization tools
Experience with machine learning, natural language processing, and large language models
Good understanding of IT processes and databases, with ability to work directly with data owners and custodians

ABOUT US

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

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 Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We're proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.

The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.