Data Scientist Team Lead

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 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.

The role provides critical feedback on translating stakeholder needs to technical specifications and oversees successful delivery.

• Lead and manage 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.
• Oversee recruitment, hiring, and onboarding of new team members.
• Conduct regular performance evaluations and provide constructive feedback.
• Develop and implement mentoring programs to support the professional growth of team members.
• Identify training needs and opportunities for skill enhancement.
• Encourage knowledge sharing and collaboration within the team.
• Collaborate with senior leadership to define data science strategies and objectives.
• Prioritize projects and allocate resources effectively to meet organizational goals.
• Monitor project progress and adjust plans as necessary to ensure timely delivery.
• Act as a liaison between the data science team and other departments.
• Understand business needs and translate them into actionable data science projects.
• Communicate project updates and insights to stakeholders at various levels.
• Establish standards and best practices for data science methodologies and workflows.
• Ensure the delivery of high‑quality analytical solutions that meet business requirements.
• Promote the adoption of robust validation and testing procedures.
• Provide 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 participate 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.
• Partner with clinicians, researchers, operational teams, and product managers to identify critical challenges, assess technical feasibility, and translate requirements into data‑driven solutions.
• Ensure 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. The candidate will be accountable for satisfying all job‑specific obligations and complying with all organization policies and procedures.

• 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)

• Minimum of 6 years of relevant experience (Required)
• Relevant experience may be a combination of related work experience and degree obtained (Master’s Degree = 2 years; PhD = 4 years)

We offer healthcare benefits for full‑time and part‑time positions from day one, including vision, dental, and domestic partner coverage.

We are proud to be an affirmative action, equal‑opportunity employer. All qualified applicants will receive consideration for employment regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.