Machine Learning Engineer (Decision Engine)

About the role

MLE on the Data Science team building and running a daily decision engine for a large consumer portfolio: propensity, timing and channel models, pipelines, monitoring, backtesting and live measurement.

Requirements

• Minimum 2 years in IT, Computer Science, Banking or Finance
• Proficiency in Python, R or Java
• Strong hands-on machine learning, statistics and experimentation
• SQL databases and statistical analysis
• Familiarity with bank products such as personal loans and credit cards preferred
• Big data processing a plus

What you'll do

• Build decisioning for account selection, channel, timing and frequency
• Build propensity, timing, channel response and contactability models and pipelines
• Build monitoring for broken inputs and model drift
• Backtest changes and measure on live traffic

Where this was posted

• LinkedIn

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