United States | Remote within GA, LA, OK, TN or TX | Direct Hire
The Opportunity
A large healthcare organization is seeking an experienced
Lead Data Scientist to lead advanced analytics initiatives involving complex structured and unstructured data.
This role combines hands-on data science, statistical modeling, machine learning, stakeholder engagement, and technical leadership. The successful candidate will partner with cross-functional teams to translate complex business challenges into analytical solutions and deliver actionable insights that support data-driven decision-making.
The position reports to the Manager of Data Science and includes responsibility for leading high-priority projects, mentoring other data scientists, and presenting analytical findings to senior leadership.
Key Responsibilities
- Lead high-priority data science and advanced analytics initiatives with organization-wide impact.
- Analyze complex, large-scale structured and unstructured data sets using advanced statistical and analytical techniques.
- Develop custom data models and algorithms to address business questions and improve operational performance.
- Build and apply predictive models and analytical approaches to key business metrics.
- Conduct research, statistical analysis, modeling, data mining, visualization, and pattern analysis.
- Develop and test hypotheses and translate findings into clear, actionable recommendations.
- Maintain existing analytical models and evaluate model performance and goodness of fit.
- Partner with cross-functional teams and internal stakeholders to identify business requirements and analytical opportunities.
- Identify, investigate, and resolve complex data quality and data availability issues.
- Improve the efficiency, scalability, and reliability of data processes.
- Manage multiple small and medium-sized analytical engagements and competing priorities.
- Provide technical guidance, coaching, and mentoring to other data scientists.
- Help educate broader audiences on data science capabilities, techniques, and developments.
- Communicate complex analytical concepts to both technical and non-technical stakeholders.
- Present analytical findings and recommendations to senior leadership.
- Assist in evaluating data science tools, platforms, and vendors.
Required Qualifications
- Bachelor's Degree in Science, Engineering, Computer Science, Mathematics, Statistics, or another related STEM discipline.
- Minimum of 7 years of professional Data Science experience.
- Strong business analytical capabilities, including process analysis, modeling, spreadsheets, procedures, and analytical problem-solving.
- Strong understanding of data architecture and design principles.
- Advanced analytical reasoning, problem-solving, and decision-making skills.
- Demonstrated ability to independently investigate complex problems and identify the information necessary to reach sound conclusions.
- Ability to manage multiple initiatives with competing priorities while meeting project goals and deadlines.
- Excellent written and verbal communication skills.
- Ability to explain complex technical and analytical information to both technical and business audiences.
- Strong stakeholder management and client-facing capabilities.
- Ability to work independently with minimal supervision in a fast-paced, multidisciplinary environment.
- Strong ability to troubleshoot issues, recommend solutions, and manage challenging stakeholder situations.
Required Technical & Analytical Experience
Candidates should demonstrate strong practical knowledge of:
- Machine learning techniques, including:
- Clustering
- Decision tree learning
- Artificial neural networks
- Understanding of the practical advantages and limitations of different modeling approaches
- Advanced statistical techniques and concepts, including:
- Regression
- Statistical distributions
- Statistical testing
- Time series forecasting
- A/B testing
- Clustering
- Predictive modeling and advanced analytics.
- Data mining, visualization, and pattern analysis.
- Advanced SQL and database management tools.
- Programming for analytical and data science applications.
- Statistical analysis tools.
- The full data science project lifecycle.
- Analysis of large, complex, and incomplete data sources.
- Model evaluation and interpretation of analytical results.
Leadership & Stakeholder Management
The ideal candidate will be able to combine technical depth with strong business communication.
The role requires the ability to:
- Translate complex data into meaningful business insights.
- Gather requirements directly from stakeholders.
- Build compelling, evidence-based data stories.
- Present findings confidently to senior and executive leadership.
- Lead cross-functional analytical initiatives.
- Mentor and provide technical guidance to less experienced data science professionals.
- Translate complex findings into clear recommendations for a broad range of stakeholders.
Preferred Experience
The following experience is preferred but not required:
- Master's Degree in Data Science.
- Professional experience within a hospital or healthcare environment.
- Medical informatics.
- Healthcare information technology.
- Healthcare finance or revenue cycle data management.
- Electronic Health Record (EHR) data management.
Candidate Profile
The strongest candidate will combine advanced quantitative expertise with strong business judgment and communication skills.
They should be comfortable moving from raw and incomplete data through statistical analysis and modeling, identifying meaningful insights, and ultimately presenting those findings in a concise and actionable manner to senior stakeholders.
A strong analytical mindset, executive-level communication capability, project ownership, and the ability to mentor others are important for success in this position.
Work Arrangement
This opportunity is remote, but candidates must be able to work from one of the following states:
- Georgia
- Louisiana
- Oklahoma
- Tennessee
- Texas
Travel of up to
20% may be required.
Work Authorization
Some visa sponsorship arrangements may be supported for this opportunity. Eligibility should be evaluated based on the individual candidate's circumstances.