Design and implement systems that combine rules, models, feature engineering, and business and product inputs into an email detection product.
Identify and recommend new features groups or ML model approaches that can significantly improve detection efficacy for a product.
Understand features that distinguish safe emails from email attacks.
Train models on well-defined datasets to improve model efficacy on specialized attacks
Actively monitor and improve False Positive rates and efficacy rates for our message detection product attack categories.

Requirements

4+ Experience with production ML systems
Fluent with Python and machine learning libraries like numpy and scikit-learn.
Experience with data analytics and wielding SQL+pandas+spark framework to both build data and metric generation pipelines, and answer critical questions about system efficacy or counterfactual treatments.
Independently responsible for the entire lifecycle of projects or features including eng design, development, and deployment.
Machine learning academic background (Bachelor's degree in Computer Science or related fields).

Benefits

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningfeature engineeringmodel trainingdata analyticsSQLpandassparkPythonnumpyscikit-learn

Soft Skills

independent project managementproblem-solvingcritical thinking

Certifications

Bachelor's degree in Computer Science