JP Morgan Chase & Co.

CCB Risk Modeling - AI ML Sr. Associate

JP Morgan Chase & Co. • $110K — $130K *
Columbus, OH 43240In-Person
Finance & Insurance
Less than 5 years of experience
Today
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Job Overview by Ladders

Qualifications

  • Ph.D. or Master’s degree in Computer Science, Mathematics, Statistics, Econometrics, or Engineering.
  • 2 years of data analysis experience in Python.
  • Experience in designing, building, and deploying machine learning models in production.
  • Knowledge of advanced machine learning algorithms such as XGBoost, CNNs, RNNs, and clustering.
  • Experience with model interpretability and explainability, especially with complex models.
  • Familiarity with large language models (LLMs) and their deployment best practices.
  • Proficient in Python, TensorFlow, PyTorch, Spark, or Scala, with knowledge of big data technologies like Hadoop.

Responsibilities

  • Design and develop machine learning models for credit and fraud decisions across the customer lifecycle.
  • Apply advanced machine learning techniques on big data to solve complex business problems.
  • Create tools for enhancing AI/ML model explainability and fairness.
  • Collaborate with senior management on modeling solutions and ensure successful deployment.
  • Partner with cross-functional teams throughout the modeling lifecycle.

Benefits

  • Opportunity to work with cutting-edge AI/ML technologies.
  • Collaborative work environment with diverse teams.
  • Focus on ethical and explainable AI practices.
  • Chance to influence key business decisions with impactful modeling solutions.
Full Job Description
JOB DESCRIPTION

Key Responsibilities

  • Model Development: Design and develop machine learning models to drive impactful decisions across credit decisions and fraud modeling, covering the entire customer lifecycle, including acquisition, account management, transaction authorization, and collections.
  • Advanced Machine Learning Techniques: Apply state-of-the-art machine learning methodologies — including deep learning architecture, transformer-based models, and LLMs — on big data platforms to tackle complex business challenges.
  • Explainability & Fairness: Develop and maintain tools and frameworks that enhance AI/ML model explainability and fairness, ensuring transparency and ethical use of models.
  • Strategic Collaboration: Work closely with senior management to develop and implement ambitious, innovative modeling solutions, ensuring their successful deployment into production environments.
  • Cross-Functional Partnership: Collaborate with diverse teams, including risk, technology, model governance, and research, throughout the entire modeling lifecycle—from development and review to deployment and operational use.

Basic Qualifications

  • Ph.D. or Master’s degree from a reputable institution in a quantitative discipline such as Computer Science, Mathematics, Statistics, Econometrics, or Engineering.
  • 2 years of experience with data analysis in Python.
  • Proven track record in designing, building, and deploying high-quality machine learning models in production environments, demonstrating a strong ability to translate theoretical concepts into practical applications.
  • In-depth knowledge of advanced machine learning algorithms, including logistic regression, XGBoost, Deep Neural Networks (CNN and RNN), clustering, and recommendation systems, with expertise in model design, hyperparameter tuning, and responsible deployment practices.
  • Demonstrated experience in model interpretability and explainability for complex models such as XGBoost and GBM; experience extending these methods to deep learning architectures (CNNs, RNNs, transformers) is a strong plus.
  • Familiarity with large language models (LLMs) and their applications, including experience in fine-tuning, prompt engineering, and responsible deployment with appropriate safeguards, monitoring, and auditability.
  • Proficiency in Python, TensorFlow, PyTorch, Spark, or Scala, coupled with experience in big data technologies such as Hadoop, AWS, and Hive, and familiarity with MLOps tooling that supports model monitoring, drift detection, and end-to-end auditability.

 

Preferred Qualifications

  • Strong expertise, interest, and track record of performing cutting-edge research on Explainable AI

(XAI) and LLM.

  • Demonstrated expertise in data wrangling and model building on a distributed Spark computation environment (with stability, scalability and efficiency). GPU experience is desired.
  • Strong ownership and execution; proven experience in implementing models in production.

About JP Morgan Chase & Co.

JP Morgan Chase & Co. stands at the forefront of the global financial services industry. They offer an expansive array of products and services to a diverse clientele, including individuals, corporations, governments, and institutions. Ever since the merger of J.P. Morgan & Co. and Chase Manhattan Corporation in 2000, this industry-leading entity has become renowned for its comprehensive portfolio encompassing consumer and community banking, corporate and investment banking, commercial banking, as well as asset and wealth management. Headquartered in the vibrant city of New York, JP Morgan Chase & Co. boasts a formidable presence across over 100 countries worldwide.

Unveiling Employment Opportunities at JP Morgan Chase & Co.

Vacancies and Hiring Initiatives

JP Morgan Chase & Co. is continuously on the lookout for talented individuals eager to contribute to its legacy of excellence. The company's recruitment efforts are geared towards identifying candidates with the right blend of skills and qualifications to drive forward its various business segments. Whether you are a seasoned professional or a recent graduate, JP Morgan Chase offers a plethora of job openings across multiple disciplines.

High-Demand Positions

Among the myriad of roles, certain positions stand out for their attractive compensation packages and career advancement prospects. Notably, high-paying jobs at JP Morgan Chase & Co. include Relationship Manager, Branch Manager, and Software Engineer. These roles are critical to the firm's operations and offer lucrative opportunities for those with the requisite expertise.

Navigating the Job Market at JP Morgan Chase & Co.

Leveraging Job Portals and Job Alerts

For job seekers aiming to tap into the opportunities at JP Morgan Chase, staying updated through job portals and subscribing to job alerts is crucial. These tools can provide timely information about job openings, job fairs, and recruitment events, enabling candidates to apply promptly and prepare adequately for interviews.

Preparing Your Job Application

Your job application, comprising your resume and cover letter, is your ticket to securing an interview at JP Morgan Chase. Highlight your qualifications, skills, and experiences that align with the job listing, ensuring you stand out in the competitive job market.

Acing the Interview

Preparation is key to succeeding in your interview with JP Morgan Chase. Familiarize yourself with the company's business segments, values, and recent achievements. Demonstrating how your background and aspirations match the company's goals can significantly increase your chances of employment. A World of Job Opportunites in the Financial Services Industry JP Morgan Chase & Co. offers a world of job opportunities for those seeking to make their mark in the financial services industry. With competitive salaries, comprehensive benefits, and endless possibilities for growth, positions at JP Morgan Chase are highly coveted. By staying informed through job sites, tailoring your applications, and preparing thoroughly for interviews, you can enhance your prospects of joining the esteemed ranks of JP Morgan Chase employees. Explore the job board, seize the job opportunities, and embark on a rewarding career journey with one of the world's leading financial institutions.
Learn more about JP Morgan Chase & Co.
Size
661 employees
Market Cap
$384.5 billion
Industry
Finance & Insurance
Net Income
$29.1 billion
Founded
1823
5 Year Trend
+0.7%
Revenue
$261.5 million
NASDAQ
CCF
* Ladders Estimates

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