Director-Data Scientist/Quality

Baptist•Memphis, TN

About The Position

The Director Data Scientist - Quality focuses on improving patient care quality through advanced analytics while optimizing revenue through quality-based payment programs. The role analyzes clinical care delivery and administrative data to identify quality improvement opportunities and help Baptist Memorial Health Care Corporation receive appropriate recognition for the high-quality care it provides. It combines analytical expertise and healthcare knowledge to predict performance in quality rating methodologies, identify improvement opportunities, and turn complex data into actionable insights for leadership and clinical teams. The position collaborates across quality, coding, clinical documentation integrity (CDI), finance, and Baptist Technology Services (BTS) to identify and integrate data sources, create analytics frameworks, and implement data-driven strategies. The Director uses large data sets to identify clinical quality optimization opportunities, tests potential approaches, and develops algorithms to monitor performance, bridging technical and clinical domains to help the organization capture revenue earned through quality care. The role provides analytical leadership for quality performance improvement, develops predictive models and early warning systems, creates dashboards and communicates findings, and supports collaboration and analytics capability development. It may include developing and supervising a team of analysts as the program demonstrates value and return on investment.

Requirements

At least 5 years of professional experience analyzing healthcare data for quality improvement and revenue optimization; 7 years preferred.
Experience with quality metrics, public reporting programs such as CMS Stars, Leapfrog, Vizient, and US News, and value-based payment programs such as HVBP, HRRP, and HACRP.
At least 7 years of data analysis experience using descriptive statistics and data exploration techniques; 8 years preferred.
Expertise analyzing complex data sets, identifying patterns and trends, and extracting actionable insights.
Demonstrated ability to integrate multiple data sources and develop analytics solutions combining clinical and financial data.
At least 3 years of experience collaborating with multidisciplinary teams such as quality, CDI, coding, finance, and IT, and working with healthcare leadership on strategic initiatives; 5 years preferred.
At least 3 years of experience creating dashboards and visualizations communicating quality performance metrics; 5 years preferred.
Experience developing and implementing predictive analytics models using deterministic and stochastic/probabilistic methods, statistical analyses, and forecasting to anticipate outcomes early enough for intervention.
Ability to translate healthcare quality methodologies into practical analytical frameworks for organizational decision-making and improvement strategies.
At least 1 year of experience mentoring analysts and collaborating on improvement initiatives; 3 years preferred.
Bachelor’s degree in data science, analytics, statistics, public health, business analytics, engineering, or a related field demonstrating strong quantitative skills.
Proficiency with SQL and at least one programming language (such as R or Python) or analytical platform (such as SAS).
Ability to work with large, complex datasets and use programming languages to manipulate data, conduct what-if scenarios, and implement predictive models.
Intermediate understanding of healthcare quality measures, terminology including DRGs, ICD-10 codes, and HCCs, clinical documentation requirements, and public reporting methodologies.
Demonstrated ability to communicate complex data insights clearly, compellingly, and actionably to diverse audiences.
Demonstrated critical thinking, ability to identify patterns in complex data, and ability to develop analytical solutions.
Curiosity, adaptability, tenacity, resilience, organization, planning, and ability to manage deadlines across multiple workstreams.

Nice To Haves

Master’s degree or PhD/Doctorate in a relevant field.
Power BI visualization experience.
Experience building and supervising analytics teams and leading improvement initiatives.
Epic Clarity and Caboodle Data Model certifications.
Databricks certifications such as Data Analyst Associate, Data Engineer Professional, and ML Engineer Professional.
Experience with SAS, R, or Python, advanced SQL skills, and experience with Epic systems.
Advanced healthcare quality knowledge and training in healthcare delivery systems, quality measures, clinical documentation, and quality-based reimbursement.
Advanced training in statistical analysis, predictive analytics, modeling, and performance evaluation.
Formal process-improvement certification, such as Lean or Six Sigma.
Advanced data storytelling skills with a proven track record of executive presentations and strategic recommendations.
Proven experience building and developing teams and applying leadership skills to cross-functional initiatives.

Responsibilities

Provide analytical leadership for the Quality Documentation Workgroup and its established improvement cycle.
Identify quality performance opportunities through comprehensive data analysis and benchmark performance against peer organizations and best practices.
Validate improvement opportunities using chart reviews and statistical analysis, support targeted solutions, and implement proactive monitoring systems.
Design sustainable analytics frameworks to maintain performance improvements.
Analyze complex healthcare data to identify quality improvement opportunities and revenue optimization strategies.
Translate CMS and other payer methodologies into analytical frameworks for organizational decision-making.
Create early warning systems that provide time to implement mitigation strategies before performance deadlines.
Design and implement statistical analyses to evaluate quality improvement initiatives.
Research and implement analytical approaches to address quality performance challenges.
Develop and implement predictive models to forecast performance in public quality rating programs and financial incentive programs.
Create and maintain dashboards and visualizations communicating quality performance metrics to stakeholders.
Present analytical findings clearly and actionably using storytelling techniques, and provide leadership with insights on optimizing quality-based payment performance.
Collaborate with quality, CDI, coding, and finance teams to integrate data sources and develop analytics solutions.
Partner with IT and data governance teams to support data integrity, appropriate access, and use of available standard platforms and tools.
Mentor and collaborate with quality analysts to build organizational analytics capabilities, with potential to develop and supervise an analyst team.
Stay current with healthcare quality measurement methodologies and payment model changes.
Identify opportunities to automate analytics processes and improve data accessibility.
Build sustainable processes for accurate documentation review and improvement.
Foster collaboration among quality, CDI, coding, and analytics teams.