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Validation Scientist

Kenvue

Lititz, PA 17543

~ 33 min OnsitePaid Time Off

A minimum of a Bachelor's degree is required.
2+ years of industry experience is required.
Knowledge related to manufacturing processes and validation is required.
General knowledge of scientific principles for liquid/semi-solid formulation development (i.e., solution, suspension, semi-solid), solid dosage development (i.e., immediate, and delayed release), and other formulation development (i.e., Nasal Spray, Eye drops, Lozenges, and sterile products), engineered products and devices as applicable
General understanding of process equipment and in-process control instruments.
General process knowledge in a few of the processes such as Mixing, Filling, Liquid dosage, Solid dosage, Liquid Packaging, Scale-up, Technology Transfer, Continued Process Verification, Process Development, as applicable.
General knowledge and understanding of equipment design, cleaning procedures, analytical methods, sampling requirements, and in the collection and evaluation of data, from the process design stage through commercial production.
General knowledge and ability to apply selected Lean tools to a situation - including: 5S, Visual Management, Mistake proofing, Kanban / rhythm wheels, and other Lean principles.
General knowledge of statistical methods such as Six Sigma, statistical tools for data analysis. (i.e., CpK, Probability of failure), and risk management tools (FMEA, etc.).
General knowledge and understanding of the Root Cause Analysis tools such as brainstorming, cause and effect analysis, fishbone diagrams, 5 why's, failure mode, effect analysis, RATIO, and others as applicable.
General knowledge of regulatory requirements in the development, validation, and manufacture of consumer cosmetic, Engineered, OTC drugs, and/or medical device products (regulatory agencies such as FDA, MHRA, Health Canada, AIFA, etc.),
General understanding of analytical skills is required.
Competent technical writing skills are required - Experience with MS Word, Excel and moderate statistic software packages is required.
Knowledge on creation of validation protocols and reports, supporting process/packaging scale-up and validation (e.g., pilot, characterization, and validation activities).