Senior Executive Manager - Data Analytics

• Develop and implement advanced data analytics and predictive modeling techniques to analyze complex datasets and to support business objectives
• Manage and analyze large datasets to identify patterns, correlations, and trends.
• Perform advanced analytics to extract actionable insights from large, structured, and unstructured data sets
• Design and maintain predictive models for risk assessment, pricing, and customer segmentation.
• Utilize data visualization tools and techniques to present findings and insights to stakeholders in a clear and compelling manner.
• Stay informed of industry trends and advancements in data analytics and predictive modeling.
• Contribute to the improvement of data quality and reliability by identifying data inconsistencies and gaps.
• Create and maintain robust data pipelines for efficient data extraction, transformation, and loading (ETL) processes.
• Ensure adherence to regulatory standards and company policies, as well as stay abreast of industry trends, technologies, and best practices in data science and health insurance.
• Collaborate with cross-functional teams to understand business requirements and deliver comprehensive analytics solutions.

Skills

• Strong academic background or relevant project/internship experience in data science or analytics.
• Proficiency in programming languages such as Python and R.
• Strong understanding of SQL and experience with database technologies.
• Familiarity with statistical software such as SAS.
• Experience with data visualization tools, preferably Power BI.
• Knowledge of data engineering principles and practices is a plus.
• A foundational understanding of statistical modeling, machine learning algorithms, and data analysis techniques.
• Team management & leadership skills.