Senior Risk ML Associate: Fraud Analytics Lead

JPMorgan Chase; Plano (TX); On-site; USD 110,000 - 150,000; Full time

Job summary

JPMorgan Chase in Plano, TX seeks a Risk program Senior Associate to lead ML-driven fraud risk ranking for transactions and new products in the Chase Consumer Bank. You will engineer features, select models, and train algorithms on data from billions of transactions.

Ideal candidates have a Master's in a quantitative field, 2+ years of Python data analysis, and hands-on ML experience (CNN/RNN/SVM, RF/GBM, RL). Preference for PhD and Spark/Hadoop in big data environments.

Qualifications

• Master's degree in Mathematics, Statistics, Economics, Computer Science, Operations Research, Physics, or related fields.
• 2+ years of experience with data analysis in Python.
• Experience designing models using ML techniques: CNN, RNN, SVM, Reinforcement Learning, Random Forest/GBM.

Responsibilities

• Identify and retool ML algorithms to analyze fraud datasets for Chase Consumer Bank.
• Perform feature engineering, selection, and train predictive models on billions of transactions.
• Collaborate with business teams to identify opportunities and guide ML solutions.
• Share findings and provide domain expertise across the firm.

Skills

Python

Data analysis

ML algorithms

CNN

RNN

SVM

Reinforcement Learning

Random Forest

GBM

Education

Master's degree in Mathematics/Statistics/CS

PhD in quantitative field (preferred)

Tools

Hadoop

Spark

Hive

Keras/TensorFlow

Job description

JPMorgan Chase in Plano, TX seeks a Risk program Senior Associate to lead ML-driven fraud risk ranking for transactions and new products in the Chase Consumer Bank. You will engineer features, select models, and train algorithms on data from billions of transactions.

Ideal candidates have a Master's in a quantitative field, 2+ years of Python data analysis, and hands-on ML experience (CNN/RNN/SVM, RF/GBM, RL). Preference for PhD and Spark/Hadoop in big data environments.