Our client is currently searching for a Senior Manager of Data Science to lead its fraud modeling team. This role is ideal for a hands-on technical leader who thrives in high-impact environments and has deep expertise in deep learning, model deployment, and cross-functional collaboration.

About the Role

You'll lead a team of data scientists focused on building and optimizing fraud detection models using advanced deep learning techniques. The team is responsible for developing proprietary models from scratch, fine-tuning client models, and deploying solutions into production environments. The ideal candidate will be a "mechanic" - someone who understands the inner workings of ML systems and can guide others through complex technical challenges.

Key Responsibilities

Lead and mentor a team of 10+ data scientists, with plans to grow to 12.
Oversee development of deep learning models using architectures like transformers, CNNs, and LSTMs.
Guide model deployment and MLOps workflows, including testing and production rollout.
Conduct code reviews and provide technical troubleshooting support.
Work with diverse data types including tabular data, text, images, and point clouds.
Collaborate with product managers, ML engineers, and client analytics teams to ensure models deliver business value.
Present technical concepts and model performance across business units.

What You'll Bring

Proven experience developing and deploying deep learning models in production.
Hands-on expertise with multiple data modalities.
Strong understanding of feature engineering, model evaluation, and deployment pipelines.
Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow).
Experience leading data science teams and staying close to technical execution.
Excellent communication skills and ability to influence cross-functional stakeholders.
Prior experience in fraud detection, risk modeling, or identity verification is a strong plus.

Compensation & Equity