Location:

Work from home (Pennsylvania)

Shift:

Days (United States of America)

Scheduled Weekly Hours:

40

Worker Type:

Regular

Exemption Status:

Yes

Job Summary:

The Data Scientist Team Lead leads a team of data scientists and analysts focusing on managing, mentoring, and developing their careers. This role emphasizes team leadership, ensuring program success, professional development, and the strategic allocation of resources to meet organizational goals. The Data Scientist Team Lead collaborates with Quality & Safety stakeholders to align team efforts with business priorities, fosters a collaborative and innovative team environment, and ensures the delivery of high-quality data science solutions. This role provides critical feedback on translating stakeholder needs to technical specifications and oversee successful delivery.

Job Duties:

• Leads and manages a team of data scientists and analysts, providing direction, support, and guidance.
• Lead evaluation of AI enabled initiatives, including impact assessment, risk analysis, and mitigation planning.
• Oversees recruitment, hiring, and onboarding of new team members.
• Conducts regular performance evaluations and provide constructive feedback.
• Develops and implements mentoring programs to support the professional growth of team members.
• Identifies training needs and opportunities for skill enhancement.
• Encourages knowledge sharing and collaboration within the team.
• Collaborates with senior leadership to define data science strategies and objectives.
• Prioritizes projects and allocates resources effectively to meet organizational goals.
• Monitors project progress and adjust plans as necessary to ensure timely delivery.
• Acts as a liaison between the data science team and other departments.
• Understands business needs and translate them into actionable data science projects.
• Communicates project updates and insights to stakeholders at various levels
• Establishes standards and best practices for data science methodologies and workflows.
• Ensures the delivery of high-quality analytical solutions that meet business requirements.
• Promotes the adoption of robust validation and testing procedures.
• Provides technical guidance in statistics, AI/ML, and software best practices. Lead code reviews and enforce best practices in coding standards, model development, and deployment processes.
• Actively participates in coding and development work (typically 50% of the time), developing and deploying robust machine learning models for diverse healthcare applications, such as risk prediction, diagnostics, treatment optimization, resource allocation and performance improvement.
• Partners with clinicians, researchers, operational teams, and product managers to identify critical challenges, assess technical feasibility, and translate requirements into data-driven solutions.
• Ensures system quality, integrity, and security by adhering to relevant Geisinger AI and data health standards and governance.

Work is typically performed in an office or remote environment. Accountable for satisfying all job specific obligations and complying with all organization policies and procedures. The specific statements in this profile are not intended to be all-inclusive. They represent typical elements considered necessary to successfully perform the job.

*Relevant experience may be a combination of related work experience and degree obtained (Master's Degree = 2 years; PHD = 4 years ).

Position Details:

Preferred Skills:

• Experience with Quality & Safety Analytics
• Databricks
• Python
• SQL
• Advanced statistical analysis
• Machine learning
• Emerging AI technologies and implementation (LLMs, RAG, GenAI, Agentic workflow integrations and deployment)

Education:

Bachelor's Degree- (Required)

Experience:

Minimum of 6 years-Relevant experience* (Required)

Certification(s) and License(s):

Skills:

Analyzing, processing and building AI/ML solutions from Clinical and Operational data sources, such as Epic Clarity, HL7, DICOM, or ECG data, Clinical Databases, Communication, Critical Thinking, Data Analysis, Data Presentations, Group Collaboration, Leadership, Machine Learning Methods, Programming Languages, Structured Query Language (SQL)