Sr. Staff ML Engineer, Risk Solutions
Define and drive the strategic vision for machine learning initiatives within the team. Lead the development and optimization of machine learning models. Oversee the preprocessing and analysis of large datasets. Deploy and maintain ML solutions in production environments. Collaborate with cross-functional teams to integrate ML models into products and services. Monitor and evaluate the performance of deployed models, making necessary adjustments. Mentor and guide junior engineers and data scientists. Ensure adherence to best practices and industry standards in ML development. Design and lead signal evaluation experiments with lift analysis, feature correlation, and predictive scoring. Build frameworks for measuring signal strength, stability (PSI), and coverage. Collaborate with risk and data teams to identify high-value signals for commercialization. 8+ years relevant experience and a Bachelor's degree OR Any equivalent combination of education and experience. Deep expertise with ML frameworks like TensorFlow, PyTorch, or scikit-learn. Extensive experience with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment. Proven track record of leading the design, implementation, and deployment of machine learning models. Familiarity with building blocks of distributed systems and technologies like GCP and Kubernetes. Excellent communication skills to translate complex analytical insights into product recommendations.
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