Kforce has an enterprise client seeking an Applied Scientist IV in Seattle, WA. Summary: As an Applied Scientist specializing in personalization, lead scoring, and complex modeling, you will tackle cutting-edge challenges in machine learning and deep learning to redefine how our business engages with customers. You will design and deploy high-impact models that drive customer segmentation, adaptive recommendations, and predictive lead prioritization. Leveraging your expertise in deep learning, NLP, and general modeling, you'll help build solutions that directly influence business outcomes, collaborating with cross-functional teams to turn novel research into scalable, production-grade systems. Responsibilities: * Lead the development of deep learning-driven personalization algorithms to deliver tailored user experiences across multiple channels (e.g., website, email and others) * Design and deploy predictive lead scoring models to optimize customer acquisition, conversion, and retention strategies using advanced techniques like survival analysis, graph networks, or transformer-based architectures * Architect end-to-end ML pipelines for large-scale deep learning models, including data preprocessing, distributed training, model optimization, and real-time inference * Publish research, file patents, and stay ahead of industry trends in the personalization and customer intelligence / lead scoring domains * Innovate in multi-modal modeling (text, graph, behavioral, and temporal data) to enhance personalization and lead scoring accuracy * Conduct rigorous A/B testing, causal inference, and counterfactual analysis to measure model impact and iterate rapidly * Collaborate with MLOps engineers to streamline model deployment, monitoring, and retraining using tools like AWS SageMaker, or MLflow and other internal tools * Participate in science reviews to raise the science bar in our organization; This includes reviewing your work and the work of others