Machine Learning Scientist - Remote

Overview

The ideal candidate will bring the excitement and passion to leverage traditional and generative AI to advance existing fraud detection mechanisms and to innovate and solve new fraud use cases. This engineer will help design, enhance, and build next generation fraud detection solutions in an agile development environment.

In Short

• Develop new models and re-train existing ones, evaluate performance, and optimize scores.
• Devise deep learning architectures and algorithms for graph-based data.
• Implement efficient methods for monitoring model effectiveness and performance in production.
• Build ETL pipelines using Spark, Python, HIVE, Scala, or Airflow.
• Experiment with and develop custom algorithms for modeling and scoring.
• Collaborate with Data Scientists, Data Engineers, Software Engineers, and cross-functional partners.

Requirements

• Minimum of 6 months of work experience or a Bachelor's Degree.
• 2 or more years of work experience preferred.
• PhD or Master’s degree in a quantitative field preferred.
• Experience in Graphical Neural Networks (GNNs) is a plus.
• Strong background in machine learning and AI algorithms.
• Proficiency in SQL and Python.
• Skilled in advanced data mining and statistical modeling techniques.
• Familiarity with Linux and commonly used IDEs like Jupyter Notebooks.

Benefits

• Comprehensive benefits package including Medical, Dental, Vision, and 401(k).
• Paid Time Off and Wellness Program.
• Potential for bonus and equity.