Senior Data Scientist - (Remote - US)

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Requirements:

• 5+ years of experience in AI, machine learning, and data science with practical deployment experience.
• Strong proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and Keras.
• Extensive experience with Kubernetes and Docker for containerized AI deployments.
• Familiarity with cloud environments (AWS preferred) for AI model deployment.
• Expertise in SQL and standard data manipulation techniques.
• Experience with anomaly detection, ideally related to financial crime patterns.
• Knowledge of MLOps, including model monitoring, retraining strategies, and production pipelines.
• Experience with AI testing platforms (e.g., MLflow) and C++ is a plus.
• A full-stack mindset, with the ability to build, deploy, and refine AI solutions in production.
• Strong customer interaction skills and the ability to translate customer needs into technical solutions.
• A Ph.D. or Master’s in Computer Science, Mathematics, Statistics, or a related field is preferred but not required.

Responsibilities:

• Develop and deploy machine learning models to detect financial crime, focusing on anomaly detection.
• Enhance and optimize data pipelines, incorporating customer feedback to improve detection accuracy.
• Lead AI model governance, ensuring models are interpretable, scalable, and reliable for real-world deployment.
• Collaborate closely with customers and stakeholders to translate feedback into technical improvements and product enhancements.
• Apply MLOps best practices to ensure smooth production-ready AI implementations.
• Provide mentorship and technical guidance to junior team members while remaining hands-on with model development.
• Stay updated on the latest AI trends and financial crime detection methodologies, continually evolving the platform's capabilities.