Data Scientist II

SWBC is seeking a talented individual who will contribute to the development of machine learning models, analytical solutions, and AI-driven capabilities that directly impact business performance and client outcomes. This role works closely with the Senior Data Scientist, Analytics Engineers, and Data Analysts to design, build, and deploy data science solutions within SWBC's modern, cloud-native data ecosystem and enterprise AI/ML platform. The Data Scientist II is expected to independently lead analyses and model development projects with minimal guidance, while contributing to the broader AI strategy of the organization. Why you'll love this role: In this role, you will work hands-on with cutting-edge tools and platforms every day, including Hex for experimentation, Omni for AI context development powering Clara, and SWBC Intelligence our multi-model AI orchestration platform spanning AWS Bedrock and AWS Sagemaker to build and deploy intelligent solutions for internal and client-facing use cases. We offer a collaborative environment that values continuous learning, empirical rigor, and professional growth. Essential duties include the following: Design, develop, and deploy machine learning models and analytical solutions to address business problems, including forecasting, segmentation, classification, and anomaly detection. Contribute to the development and enhancement [... source excerpt omitted ...] n quality. Perform AI experimentation and prototyping within governed sandbox environments, including Snowflake Sandbox and Hex, ensuring adherence to data privacy and compliance requirements. Apply Responsible AI principles, including bias detection, model explainability, and fairness monitoring, to all model development activities. Collaborate with cross-functional teams including Analytics Engineering, Data Management, and business stakeholders to translate business problems into data science solutions. Communicate findings, model results, and recommendations to both technical and non-technical audiences through clear documentation, visualizations, and presentations. Stay cur [... source excerpt omitted ...] g trends in data science, machine learning, and AI, and contribute to the team's knowledge sharing and continuous improvement culture. Serious candidates will possess the minimum qualifications: Master's degree in a quantitative field such as Computer Science, Data Science, Statistics, Mathematics, or a related discipline. Equivalent professional experience (5+ years) may be considered in lieu of an advanced degree. Minimum of two (2) years of progressive experience in data science, analytics, or machine learning roles. Proficiency in Python and SQL, with working knowledge of ML frameworks such as TensorFlow, PyTorch, scikit-learn, or equivalent. Experience developing and deployin