Process Development, Data Scientist II
Forge Biologics
- Columbus, OH
- Permanent
- Full-time
- Focus on extracting insights from production data to identify areas for improvement, predict potential issues, drive efficiency, automate data pipelines, and create insightful dashboards to support development and manufacturing.
- Lead data structuring, perform data analysis to build data trends and patterns, model development, and statistical analysis.
- Ensure innovative technologies and methodologies are employed to maintain the highest data quality standards while ensuring that activities occur in an efficient and GDP-compliant manner.
- Generate reports and contribute to responses to both internal and external stakeholders.
- Independently present results, work with cross-functional teams where necessary to prepare publications or reports in alignment with key stakeholders.
- Become a subject matter expert (SME) for our electronic lab notebook system, Benchling, our documentation and training system, Quality Management System (Veeva).
- Work closely with process development scientists to apply advanced data analytical techniques to understand and optimize the manufacturing process.
- Providing training to process development team members on data science and analytics including but not limited to the training curriculum.
- Review study protocols, and technical reports and approve documentation.
- Ensure reports are written to highest standards and manage documentation review and approvals to meet deadlines.
- Ensure data is maintained in an accurate and controlled manner.
- Support internal process transfer activities from Process Development to GMP.
- Provide training, leadership, and guidance to the team, share resources on best practices, and provide feedback.
- Effectively manage a team of Data Scientists to support process development needs.
- Provide technical guidance and mentorship to junior team members, promoting their personal growth and skill development.
- Collaborate closely with process development scientists, Manufacturing Sciences and Technology, cGMP, Compliance and Information technology teams to manage on the projects while adhering to relevant standards and company guidelines during product lifecycle.
- Bachelor's degree in chemical engineering, Biomedical Engineering, Biology or related discipline (or equivalent experience) with a minimum of 10 years' experience.
- Experience in Data Science, Data Analytics, Data Engineering, or related discipline certification, or relevant coursework are a plus.
- Working knowledge of purification techniques such as chromatography, tangential flow filtration, clarification etc. is a plus.
- Understanding of manufacturing processes relevant to the industry (e.g., chemical engineering, pharmaceutical production)
- Knowledge of process control methodologies and quality standards.
- Proven ability to operate and troubleshoot purification equipment.
- Experience in planning, conducting, and reviewing experimental data with no oversight.
- Prior experience in training and development of other team members.
- Proven ability to manage team members effectively.
- Experience in analyzing datasets and utilizing the corresponding data to influence decision making.
- Skilled at organization and managing multiple projects simultaneously.
- Strong analytical and data interpretation skills to assess and drive quality improvement through the analysis of quality metrics and performance data.
- Experience working with at least two of the following: Benchling, Excel, JMP, SQL, or Power BI.
- Robust understanding of regulatory requirements as they pertain to process development and characterization.
- Excellent communication and collaboration skills to work effectively with cross-functional teams and to convey complex data insights to stakeholders.
- Problem-solving and critical thinking skills to identify root causes and propose solutions.
- Experience in leading, mentoring, and guiding junior team members.
- Strong understanding and experience in Electronic Quality Management Systems (EQMS), Laboratory Information Management Systems (LIMS), etc.and regulatory requirements relevant to the industry.
- Master's Degree or PhD in Chemical Engineering, Biomedical Engineering, Biology, or related discipline (or equivalent experience).
- Experience working with viral vectors (AAV, Lentivirus, etc.).
- Experience directly managing junior team members.
- Previous data or Software Engineering role in Biology, Chemistry, or other Life Science Industry.
- Proficiency in Python, R, and SQL, Predictive modeling, hybrid modeling
- Experience in machine learning algorithms (regression, decision trees, neural networks)
- Familiarity with big data tools and cloud platforms (AWS, Azure)