Full Time Advanced Analytics Jobs Near Me

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

JOB DESCRIPTION

If you are passionate about leveraging advanced analytics and AI to combat fraud and drive business value, we encourage you to apply!

As a Senior Quantitative Analytics Associate in our Fraud Risk team, you will help prevent plastics fraud through advanced, data-driven analysis. You'll gain a comprehensive understanding of the point-of-sale transaction lifecycle and deliver timely, efficient, and tailored solutions. You will collaborate with cross-business partners to leverage advanced analytics for fraud/scam prevention, dispute and claim management, and optimization of risk/reward tradeoffs (losses/OpEx/customer experience), with the goal of driving positive business outcomes.  

Job Responsibilities

• Analyze large datasets to detect patterns, trends, and anomalies indicative of fraudulent activity.
• Build, develop, and maintain reporting and data automation systems to communicate insights to leadership for strategic decision-making.
• Enhance internal analytical techniques and introduce best practices to improve key business metrics.
• Work independently and collaboratively with cross-functional partners, from problem identification to data analysis and delivering actionable recommendations.
• Develop and implement GenAI and Agentic AI solutions using Python to automate and optimize decision-making processes.
• Apply large language models (LLMs), machine learning (ML) techniques, and statistical analysis to improve decision-making and workflow efficiency across fraud operations and customer experience.
• Design and demonstrate proof-of-concepts (POCs) for extracting insights from structured and unstructured data using advanced analytics; build and iterate on prototype solutions.
• Stay current with the latest research in LLM, ML, and data science, and leverage emerging techniques for ongoing enhancement.

Required Qualifications, Capabilities, and Skills

• Advanced degree in a quantitative discipline (e.g., Computer Science, Mathematics, Operations Research, Data Science).
• 3+ years of experience in Risk Management or any quantitative field
• Hands-on experience with SQL, Python, and Alteryx.
• Strong understanding of the foundational principles and practical implementation of machine learning algorithms for anomaly detection, including clustering, classification, neural networks, distance-based, and time series methods.
• Experience creating generative AI solutions using LLM prompt engineering and Retrieval Augmented Generation (RAG).
• Experience with evaluation metrics for ML and generative AI.
• Demonstrated ability to communicate complex concepts and results to both technical and business audiences.

Preferred Qualifications, Capabilities, and Skills

• Hands-on experience with behavioral and transactional analytics tools and techniques.
• Familiarity with model explain ability and self-validation techniques.
• Preferred experience supporting more than one CCB Operations Function/Line of Business.

This role is not eligible for visa sponsorship.  This role is 5 days a week full time in office.

ABOUT US

Chase is a leading financial services firm, helping nearly half of America's households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

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.

Equal Opportunity Employer/Disability/Veterans

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.