Senior Data Scientist - (Remote - US)

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.

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.