Data Scientist

Repost of AMAGJP Please no candidates from that last posting.
Hybrid at Thousand Oaks. Expectation is 3 days onsite per week.
The ideal candidate is a Data Scientist with a strong engineering background, preferably in Mechanical, Biomedical, or Chemical Engineering, with proven experience in simulation, modeling, and data analysis within a GMP-regulated environment. They are proficient in Python, MATLAB, and Minitab, and possess a deep understanding of engineering principles applied to physical systems. The candidate holds either a PhD with no required industry experience, a Master's degree with at least 2 years of experience, or a Bachelor's degree with a minimum of 4 years of experience. They are highly analytical, collaborative, and adaptable, with the ability to translate experimental data into actionable insights. Candidates with degrees in Computer Science, Electrical Engineering, or Computer Engineering, or those with purely software-focused backgrounds, are not a fit for this role.
The Digital Data Scientist will support the Combination Product Operations organization by improving the way *** manages and utilizes data to enhance data analysis and decision making within the organization. We are seeking a highly motivated individual who will be primarily responsible for development and lifecycle management of digital modeling assets and analyzing scientific and combination product performance data. This individual will leverage in-silico and data-driven modeling to evaluate potential opportunities that enable changes in business and operation performance.
The ideal candidate enjoys tackling challenges and excels at enabling insights for decision making using data-driven and physics-based modeling.
This may include, but is not limited to, the following:
• Applying engineering principles to develop in-silico models for combination products
• Developing, enhancing, automating, and managing analytics and data-driven models
• Performing ad-hoc analysis and supporting special projects; Providing input to management for trend and failure investigation process improvements
• Demonstrating modeling and visualization approaches as part of proof-of-concept projects
• Transforming ambiguous business and technical questions into measurable and impactful projects
• Demonstrating critical and analytical thinking skills to explore new opportunities in in-silico and data-driven models for combination products.
Skills:
Experience with programming in Python, MATLAB, JMP, and/or Minitab for engineering purposes
Experience with model simulation and analysis (MS&A) techniques for structural, fluidic, and heat