Healthcare Data Scientist - Enterprise

at  University of Alabama at Birmingham

MINIMUM REQUIREMENTS

Master’s or Ph.D. in Data Science, Statistics, Computer Science, or a related field and three (3) years of experience in data science, preferably in a healthcare or operations setting.

KNOWLEDGE/SKILLS/ABILITIES

• Demonstrated experience with machine learning algorithms and statistical modeling techniques.
• Proven track record of developing and deploying predictive models in a real-world environment.
• Proficiency in programming languages such as Python, R, or SQL.
• Experience with data visualization tools like Tableau, Power BI, or similar platforms.
• Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud computing (AWS, Azure, or Snowflake).
  Primary Location: UAB Hospital
  Job Category: Information Technology
  Organization: 702150000 Health System Information Services
  Employee Status: Regular
  Job Level: Mid-Level
  Shift: Day/1st Shift

GENERAL RESPONSIBILITIES

The Data Scientist will play a pivotal role in analyzing and interpreting complex data sets to enhance the efficiency of clinical operations and improve patient care outcomes. This role requires a strong foundation in machine learning, statistical concepts, and data science methodologies. The Data Scientist will collaborate with healthcare professionals, operations teams, and IT departments to develop predictive models, optimize processes, and support data-driven decision-making.

KEY DUTIES & RESPONSIBILITIES

1. Analyze large datasets to identify trends, patterns, and opportunities for clinical operational improvement.
2. Develop and implement machine learning models to predict patient outcomes, optimize resource allocation, and enhance clinical operational efficiencies to recognize patterns.
3. Apply advanced statistical methods to evaluate the effectiveness of interventions and care protocols.
4. Identify opportunities for process improvement and pose relevant business questions that lead to valuable insights.
5. Analyze large datasets to identify trends, patterns, and opportunities for clinical operational improvement.
6. Develop and implement machine learning models to predict patient outcomes, optimize resource allocation, and enhance clinical operational efficiencies to recognize patterns.
7. Apply advanced statistical methods to evaluate the effectiveness of interventions and care protocols.
8. Identify opportunities for process improvement and pose relevant business questions that lead to valuable insights.
9. Work closely with clinical teams to understand patient care processes and identify areas for improvement.
10. Partner with operations and clinical teams to develop data-driven solutions that enhance workflow efficiency and reduce costs.
11. Collaborate with IT and data engineering teams to ensure the integrity and accessibility of data.
12. Create comprehensive reports and visualizations to effectively communicate findings to health system leadership.
13. Present data-driven recommendations to leadership to support strategic decision-making.
14. Develop dashboards and tools tp provide insights into key performance metrics.
15. Stay current with latest developments in data science, machine learning, and healthcare analytics.
16. Lead and contribute to research initiatives, as needed, aimed at improving patient care through innovative data applications.
    Qualifications