• Serve as Lead Data Scientist within the Enterprise Data and Analytics team, helping to build and develop the data science function. • Prioritize and manage multiple analytical projects based on business value and technical feasibility. • Design, build, and deploy large-scale data-driven models using advanced statistical, machine learning, and AI techniques. • Lead experimentation and research on cutting-edge machine learning and deep learning methodologies. • Act as the subject matter expert and resource for machine learning solutions across diverse business needs. • Own the end-to-end model development lifecycle, including requirements gathering, data sourcing, model fitting, presentation, and production deployment. • Mentor, coach, and provide leadership to junior team members; foster team development across the organization. • Collaborate with stakeholders to understand business objectives and ensure analytics solutions align with organizational needs. • Evangelize best practices and drive adoption of analytics within product and analytics teams. • Stay current with emerging technologies, anticipate trends, and assess their potential impact on business solutions. • Communicate complex technical results effectively to both technical and non-technical audiences. • Utilize expertise in various data science and machine learning tools (e.g., Python, R, SAS, SQL, TensorFlow, AWS Sagemaker). • Leverage both structured and unstructured data sources for predictive modeling and analytics. • Preferably possess a background in Financial Services. • Education: Bachelor’s, Master’s, or PhD in computer science, statistics, economics, or related field. • Experience: 5+ years relevant work using statistics, machine learning, and big data tools to solve business problems and deploy models.