Sr Manager-Data Science

Job Summary

The Sr Manager-Data Science will play a pivotal role in driving data-driven decision-making processes within the organization. With a focus on the Payer domain the candidate will leverage their extensive experience in Data Science to enhance business strategies and outcomes. This hybrid role requires a seasoned professional with a deep understanding of data analytics machine learning and statistical modeling to lead and innovate in a dynamic environment.

Responsibilities

• Lead the data science team to develop innovative solutions that enhance business strategies in the Payer domain.
• Oversee the design and implementation of data models and algorithms to solve complex business problems.
• Provide strategic insights by analyzing large datasets and identifying trends and patterns.
• Collaborate with cross-functional teams to integrate data science solutions into business processes.
• Ensure the accuracy and reliability of data-driven insights by maintaining high standards of data quality.
• Drive the adoption of advanced analytics and machine learning techniques across the organization.
• Develop and maintain dashboards and reports to communicate findings to stakeholders.
• Mentor and guide junior data scientists to foster a culture of continuous learning and improvement.
• Evaluate and implement new data science tools and technologies to enhance team capabilities.
• Work closely with IT and data engineering teams to ensure seamless data integration and accessibility.
• Monitor industry trends and advancements in data science to keep the organization at the forefront of innovation.
• Establish best practices for data governance and security to protect sensitive information.
• Contribute to the companys purpose by using data science to improve healthcare outcomes and efficiencies.

Qualifications

• Possess a strong background in data science with a minimum of 16 years of experience in the field.
• Demonstrate expertise in the Payer domain with a deep understanding of industry-specific challenges and opportunities.
• Exhibit proficiency in machine learning statistical modeling and data analytics.
• Have experience in leading and managing data science teams in a hybrid work model.
• Show capability in collaborating with cross-functional teams to drive data-driven decision-making.
• Display strong problem-solving skills and the ability to translate complex data into actionable insights.