Data Scientist

• Design, develop, and evaluate machine learning, statistical, and predictive models to solve complex business challenges across multiple departments.
• Apply modern artificial intelligence and machine learning techniques, including large language models (LLMs), generative AI, and advanced analytics, to automate processes, enhance decision-making, and generate business insights.
• Translate business objectives into well-defined analytical, statistical, and machine learning solutions that deliver measurable business value.
• Analyze large, complex datasets to identify trends, patterns, opportunities, and operational improvements.
• Partner with data engineering, IT, and business teams to develop scalable data pipelines and deploy machine learning models into production environments.
• Evaluate data quality, model performance, and AI system limitations while ensuring responsible, ethical, and practical implementation of predictive models.
• Present analytical findings, recommendations, and technical concepts clearly to executive leadership and both technical and non-technical stakeholders.
• Develop, monitor, and optimize predictive models, ensuring ongoing performance, accuracy, and reliability through continuous improvement.
• Stay current with emerging technologies, AI advancements, machine learning methodologies, and data science best practices to identify opportunities for innovation.
• Collaborate across departments to support strategic initiatives, business intelligence projects, forecasting, automation, and operational optimization.
• Maintain thorough documentation of models, methodologies, assumptions, and development processes to support transparency, reproducibility, and governance.
• Support ad hoc analytical projects and provide data-driven recommendations that improve business performance and operational efficiency.