Job Description

Inteldot

has over 14 years in the life science industry with allocations across Puerto Rico, the United States, Europe, and Japan. This is a great opportunity for one of our leading clients Segoe UI in

Puerto Rico

.

Administrative Shift

Description:

To conceive, design, implement and execute specific scientific experiments, which contribute to the successful completion of goals and/or projects under general guidance of supervisor.

Responsibilities:

Designs, monitors, or conducts strategies with general guidance from the supervisor. Provides data analysis and interpretation and assesses the impact of the data on the project. Keeps current in technical expertise and areas relevant to their function. Monitors field of expertise, including literature and technology development, and communicates relevant observations. Develop and implement new and novel protocols to address specific issues. May represent the department on project teams under the supervision of a senior scientific staff member. May initiate productive collaborations within and outside of the department or company. Advises or assists others in experimental design and/or interpretation/diagnosis of data and implementing innovative remedies. Able to develop solutions to routine technical problems of limited scope. Comprehensive understanding of validation protocol execution requirements. In-depth knowledge of validation processes as applied to new equipment installations.

Job Requirements:

Automated Visual Inspection (AVI) Expertise (Key Differentiator - Highly Desired) Direct experience with automated visual inspection systems, such as:
+ Machine vision-based inspection platforms
+ Camera systems, lighting optimization, optics
+ Image acquisition and defect detection logic
Knowledge of AVI system qualification and validation:
+ IQ/OQ/PQ
+ Performance qualification using defect kits
Experience developing or supporting:
+ Inspection recipes
+ Defect libraries and defect standards
+ Sensitivity and false reject optimization
+ Familiarity with manual vs automated inspection correlation
+ Data, Statistics & Digital Skills (Preferred)
Strong statistical background, including:
+ Sampling plans (AQL, zero acceptance, etc.)
+ Inspection capability studies
+ Measurement system analysis (MSA)
Experience with data analysis tools:
+ JMP, Minitab, Python, or equivalent
Comfort working with large inspection datasets to:
+ Trend defect rates
+ Support process improvements
+ Drive inspection strategy decisions

E

ducation:

Doctorate or master + 2 years of Scientific experience or Bachelors + 4 years of Scientific experience. Chemical Engineering, Mechanical Engineering, Biomedical Engineering, Materials Science, Pharmaceutical Sciences, or related field. * Training in vision systems (i.e., Cognex, Systech, Syntegon, Koerber, A3 CVP, PDA 593)