Senior Risk ML Scientist: Real-Time Fraud Detection

Quiet Capital; Canada; On-site; CAD 157,000 - 237,000; Full time

Job summary

Mercury is seeking a Machine Learning-focused Data Scientist to bolster our Risk team. You will build, validate, and deploy real-time fraud detection models while ensuring data quality across pipelines in a fast-paced fintech environment.

You will collaborate with Risk Strategy and Engineering to improve model inputs, governance, and observability, delivering a trustworthy banking experience for customers.

Qualifications

• 5+ years of experience working with and analyzing large datasets to solve problems and drive impact, with 3+ years of ML experience.
• Proficiency in SQL and experience using it to understand and manage imperfect data.
• Proficiency in Python and experience with statistical modeling and machine learning.
• Experience deploying and monitoring machine learning models in production.

Responsibilities

• Build, validate, and deploy machine learning models to identify and prevent fraud in real time.
• Support the reproducibility and robustness of said models through documentation, testing, and monitoring.
• Ensure data quality and reliability across pipelines and tools.
• Collaborate with Risk Strategy to ideate on model inputs and applications and with Engineering to optimize deployment and observability.

Skills

SQL

Python

Machine Learning

Production ML deployment

Data quality

Tools

dbt

ETL

Job description

Mercury is seeking a Machine Learning-focused Data Scientist to bolster our Risk team. You will build, validate, and deploy real-time fraud detection models while ensuring data quality across pipelines in a fast-paced fintech environment.

You will collaborate with Risk Strategy and Engineering to improve model inputs, governance, and observability, delivering a trustworthy banking experience for customers.