Digital Plant Representative-Technical Services/Engineering
IE: Kinsale
Eli Lilly and Company
Lilly is a medicine company turning science into healing to make life better for people around the world.At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.
Responsibilities:
- The digital plant representative will primarily be responsible for supporting the implementation of robust control strategies in continuous manufacturing processes through digital solutions including the use of models. The digital plant representative will combine manufacturing understanding, analytical tools, data handling, statistics,, chemistry and chemical engineering first principles ,modelling and data visualization skills to deliver a robust control strategy for supply and new products. A major part of the role will involve developing, implementing and maintaining material tracking models to support the batch release process. This will involve close collaboration with process teams, modelling SMEs, development, IT, engineering and automation to develop models and identify appropriate tools for data acquisition, aggregation and reporting to ensure API’s are manufactured in a safe, compliant and consistent manner.
The role will be located in the new manufacturing site in Lebanon, Indianapolis, however the first 12 months minimum, will be located in Eli Lilly Kinsale Ireland.
Duties include:
- Ensure the process is in-control, capable, compliant and maintained in a validated state by developing digital solutions for data analysis and process monitoring.
- Work with development, IT, statistics & Automation to develop, implement and integrate models for material tracking/batch genealogy and control strategy purposes in a CGMP environment.
- Work with the Engineering Technical Centre to build the material tracking model using mathematical equations that represent the fluid dynamics for dispersion in a flow system
- Work with operations and the process team to develop and execute protocols to gather data to support the model build and model verification.
- Own the documentation and any calculations required to verify the material tracking model represents the equipment set being built in the Lebanon facility.
- Work with development, IT & Automation to identify and implement appropriate solutions for analytical and parametric data management and analysis using appropriate tools (Python, SIMCA, R etc).
- Work with QA, operations and the process teams to develop and implement business processes for the use of models and digital solutions in manufacturing.
- Work with the process teams to develop and maintain models in a verified state .
- Provide training on the material tracking model for new model users and support model owners to maintain the model in a verified state.
- Implement ongoing monitoring plans for the material tracking model to ensure it remains in a verified state and data integrity is maintained.
- Build technical expertise in the area of responsibility and demonstrate strong data-driven decision-making and problem-solving capabilities.
- Provide support to the business in use of material tracking systems to release production batches
Basic Qualifications:
Educational Requirements:
PhD in Chemistry (Organic / Synthetic / Medicinal / Analytical) or Engineering. BSc or BEng with relevant experience.
Experience Requirements:
1-2 years industrial experience is desirable but not essential.
Additional Skills/Preferences
- Deep technical interest and understanding in the field of manufacturing science.
- Strong analytical and problem solving skills.
- Strong collaborative skills with an ability to work effectively in a team environment.
- Demonstrated strong verbal and written communication skills.
- Demonstrated ability to participate in and facilitate decision-making.
- Experience in statistics, data integrations, analysis and visualization.
- Experience in building models e.g. chemometric models for managing and using PAT data.
- An understanding of automated manufacturing control systems.
- Prior experience with analysis or modelling of continuous processes.
- Experience working with cross-functional teams, including Quality, Manufacturing Technical Support, Facilities and Engineering and Validation.
- Experienced in troubleshooting, investigation, root cause and risk analysis in a CGMP environment
Additional Information
In carrying out his/her responsibilities, the Digital Plant Representative is expected to partner with Development Scientists, Kinsale Technical Services Laboratory, Engineering, Operations, Materials Management, Quality & Regulatory, IT & Automation to develop and implement digital solutions to support a robust control strategy. He/she must have the interpersonal skills required to work effectively with a broad spectrum of people.
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs Chemistry Data analysis Data management Data visualization Engineering Industrial PhD Python R Statistics
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