The Role
Lead AI-enabled optimization and resource planning initiatives for drug product manufacturing. Collect, clean, analyze, and visualize operational data; develop automation and digital workflows; support validation and GMP documentation; perform statistical/process evaluation; engage stakeholders and translate business needs to technical solutions. May support non-standard shifts.
Summary Generated by Built In
- The ideal candidate should demonstrate a strong combination of technical, analytical, and operational skills to support AI-enabled optimization, resource planning, and validation-related initiatives within Drug Product.
- A standout candidate would have experience or demonstrated capability in the following areas:
- Data analytics and visualization.
- Ability to collect, organize, clean, analyze, and interpret complex operational or manufacturing data. Experience with tools such as Excel, Power BI, Smartsheet, JMP, Minitab, or similar platforms would be highly valuable.
- Programming, automation, and AI-enabled tools.
- Foundational programming or automation experience, including exposure to Python, Codex, AI-assisted coding tools, Power Automate, scripting, database structure, or digital workflow development. The candidate does not need to be an expert programmer but should be comfortable learning and applying digital tools to solve business problems.
- Statistical and process evaluation mindset.
- Understanding of basic statistics, process variability, trending, capacity evaluation, data comparison, and performance monitoring. This would support both workload forecasting and characterization/validation data evaluation.
- Validation and/or GMP documentation experience.
- Knowledge of GMP expectations, validation lifecycle activities, protocol/report development, documentation practices, data integrity, discrepancy follow-up, and compliance-driven execution.
- Strong communication and stakeholder engagement.
- Ability to work with cross-functional teams, gather user requirements, translate business needs into tool requirements, and communicate findings clearly to management and technical stakeholders.
- Be available to support non-standard shift when activities are required.
Requirements
MUST qualify in the categories as follows:
Doctorate OR Masters + 2 years of data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science or related field experience OR
Bachelors + 4 years of data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science or related field experience OR
Associates + 8 years of data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science or related field experience OR
High school/GED + 10 years of data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science or related field experience
- The following educational backgrounds may be considered, provided the candidate’s experience meets the role requirements: Industrial Engineering, Systems Engineering, Computer Science, Chemical Engineering, Biomedical Engineering, Biotechnology, Manufacturing Engineering, or a related technical discipline.
- A background in Engineering is highly preferred due to the project’s focus on resource planning, workload modeling, capacity evaluation, process optimization, and operational efficiency. However, candidates from science, or data-focused backgrounds may also be strong fits if they demonstrate experience with data analytics, digital tools, GMP operations, and validation support.
Skills Required
- Education/experience: Doctorate OR Masters +2 years OR Bachelors +4 years OR Associates +8 years OR High School/GED +10 years in data science, statistics, applied mathematics, business analytics, engineering, computer science or related field
- Data analytics and visualization experience
- Ability to collect, organize, clean, analyze, and interpret complex operational or manufacturing data
- Experience with Excel, Power BI, Smartsheet, JMP, Minitab, or similar platforms
- Programming, automation, and AI-enabled tool experience
- Exposure to Python, Codex, AI-assisted coding tools, Power Automate, scripting, database structure, or digital workflow development
- Statistical and process evaluation mindset
- Understanding of basic statistics, process variability, trending, capacity evaluation, data comparison, and performance monitoring
- Validation and/or GMP documentation experience
- Knowledge of GMP expectations, validation lifecycle activities, protocol/report development, documentation practices, data integrity, discrepancy follow-up, and compliance-driven execution
- Strong communication and stakeholder engagement skills
- Ability to work with cross-functional teams, gather user requirements, translate business needs into tool requirements, and communicate findings to management and technical stakeholders
- Availability to support non-standard shift when activities are required
- Background in engineering (Industrial, Systems, Chemical, Biomedical, Manufacturing) or related technical discipline
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The Company
What We Do
ISPV Inc. is a Life Science company that leads Productivity & Validation projects for the Pharmaceutical and Food industries.
