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.
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