Responsibilities:
- Lead and mentor a team specializing in data engineering, data science, software development, and predictive sciences; drive effective employee development.
- Design, implement, and optimize modern automated data pipelines for seamless data flow, integration, and accessibility across scientific and operational domains.
- Create data visualization platforms and dashboards to support decision-making and democratize analytics for scientists and business partners.
- Champion development and deployment of in silico modeling.
- Partner with operational subject matter experts to develop and implement change management strategies.
- Clarify digital business value, establish, and measure project metrics aligned with program goals.
Education Minimum Requirement:
- PhD, MS, BS, or equivalent experience in chemistry, engineering, data science, computer science, or a related scientific discipline
- BS +9 years; MS +8 years; PhD +6 years
- Experience spanning pharmaceutical development, scientific data/analytics, analytical characterization, and digital insights.
Required Experience and Skills:
- Ability to translate complex scientific or business problems into digital solutions.
- Strong people leadership, influencing, and change-management skills.
- Excellent communication, creativity, and interpersonal skills.
Preferred Experience and Skills:
- CMC experience across drug substance, drug product, and analytical methods.
- Data analysis and modeling workflows/solutions (including machine learning).
- Experience with drug modalities (small molecule, biologics, vaccines, peptides, drug conjugates).
- Programming in R and/or Python (Posit/RStudio/Jupyter).
- Data visualization tools (Shiny, Streamlit, Spotfire, Dash, PowerBI, Tableau).
- Prior people management/mentorship; cross-functional teamwork; scientific curiosity; peer-reviewed publications/external presentations.