Senior Fraud Risk ML Engineer

Next Frontier Capital; Plano (TX); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Comprehensive health care coverage

Retirement savings plan

On-site health and wellness centers

Backup childcare

Tuition reimbursement

Mental health support

Financial coaching

Job summary

Chase is seeking a Risk program Senior Associate to enhance fraud risk ranking through ML algorithms. You will engineer features, select models, and train predictive systems on billions of data points.

Collaboration with business teams will translate needs into scalable ML solutions. Qualified candidates have a Master's in a quantitative field and 2+ years Python data analysis experience, with familiarity in Hadoop/Spark and TensorFlow/Keras optional.

Qualifications

• Master's degree in quantitative fields and 2+ years of Python data analysis.
• Experience designing models for commercial use with ML techniques (CNN/RNN/SVM/GBM).
• Interest in model behavior and practical design considerations.

Responsibilities

• Identify and retool ML algorithms to analyze fraud datasets for Chase Consumer Bank.
• Perform feature engineering, selection, and train predictive models on large datasets.
• Collaborate with business teams to translate needs into ML solutions.
• Share findings and provide domain expertise across the firm.

Skills

Python

ML algorithms

Feature engineering

Data analysis

Big data awareness

Education

Master's degree in quantitative field

Tools

Hadoop/Spark

Keras/TensorFlow

Job description

Chase is seeking a Risk program Senior Associate to enhance fraud risk ranking through ML algorithms. You will engineer features, select models, and train predictive systems on billions of data points.

Collaboration with business teams will translate needs into scalable ML solutions. Qualified candidates have a Master's in a quantitative field and 2+ years Python data analysis experience, with familiarity in Hadoop/Spark and TensorFlow/Keras optional.