Machine Learning Engineer - Fraud Detection

What role you will play in team

You'll be part of a team building machine learning models to detect and prevent fraudulent activities.

What you will do

You'll design, develop, and deploy machine learning models to identify fraudulent transactions in real-time.

Key responsibility

• Develop and implement machine learning models for fraud detection using various algorithms (e.g., anomaly detection, classification).
• Evaluate model performance and continuously improve accuracy and efficiency.
• Work with large datasets and handle imbalanced data.
• Collaborate with engineering and product teams to integrate models into production systems.
• Stay up-to-date with the latest advances in fraud detection and machine learning.

Required Qualification and Skills

• Bachelor's or Master's degree in Computer Science, Statistics, or related field.
• Strong programming skills in Python or similar language.
• Experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch.
• Experience with big data technologies (Spark, Hadoop) is a plus.
• Understanding of fraud detection techniques and methodologies.

Benefits Included

• Competitive salary and comprehensive benefits package.
• Opportunities for professional development and growth.
• Challenging and impactful work in a dynamic environment.

A Day in the Life

A day might involve data exploration, model training, performance evaluation, and collaboration with cross-functional teams.