Description

You will apply advanced statistical and machine learning techniques to solve complex risk and anomaly detection problems.

This role is hybrid.

Responsibilities

• Apply statistical, machine learning, and graph analytics techniques to solve risk and anomaly detection problems.
• Design and evaluate predictive models using Precision@K, ROC-AUC, and F1-score metrics.
• Translate model insights into clear, explainable outputs for non-technical stakeholders.
• Utilize transformer-based NLP models for sentiment analysis and entity resolution.

Required Skills

• 5+ years applying advanced statistical, machine learning, and graph analytics techniques.
• Strong proficiency in Python, including PyTorch and TensorFlow.
• Expertise with Scikit-learn and other ML frameworks.
• Demonstrated experience with transformer-based NLP models.
• Ability to evaluate predictive models against business impact.
• Any Graduate education required.

Preferred Skills

• Hands-on experience in fraud detection or national security risk modeling.
• Experience modeling complex supply chains using graph-based ML.

Key Skills

Education

Any Graduate