Data Scientist, Medical Device & Mathematical Modeling; JP

Overview

Job Title: Data Scientist, Medical Device & Mathematical Modeling (JP12081)

Location: Thousand Oaks, CA. 91320

Business Unit: Combination Products Operations – Digital & Data Strategy

Employment Type: Contract

Duration: 1+ years (with possible extensions)

Rate: $52 - $56/hr

Posting Date: 1/5/2024

Notes: Only qualified candidates need apply. Onsite 3-4x / week.
Must be OK to be onsite weekly and must be local to Thousand Oaks, CA.

The Modeling and Simulation Data Scientist will support the Combination Product Operations organization by improving the way our client 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.

• Simulation, modeling, and data analysis experience
• 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 transfer problems using commercial software such as ANSYS, LS-Dyna, ABAQUS, COMSOL
• Experience with mathematical/first principles modeling, numerical techniques, and uncertainty quantification such as Monte Carlo simulations

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

• Doctorate degree OR Master degree and 3 years of experience OR Bachelor degree and 5 years of experience OR Associate degree and 10 years of experience OR High school diploma / GED and 12 years of experience
• Experience with model simulation and analysis (MS&A) techniques for structural, fluidic, and heat transfer problems using commercial software such as ANSYS, LS-Dyna, ABAQUS, COMSOL
• Experience with programming in Python, MATLAB, JMP, and/or Minitab for engineering purposes
• Experience with mathematical/first principles modeling, numerical techniques, and uncertainty quantification such as Monte Carlo simulations
• Familiar with utilizing Git Lab for version control, code collaboration, and project management
• Data analysis expertise and statistical or mechanistic modeling experience
• Experience in deriving technical recommendations and specifications from the analysis of measured data
• Strong communication, presentation, and technical documentation skills are a plus, as is knowledge of process controls
• Understanding business needs and developing novel yet practical solutions to meet those needs
• Experience with combination products and device regulatory requirements and medical device development and engineering

• Passion for proactively identifying opportunities through creative modeling and data analysis
• Transform ambiguous business and technical questions into measurable and impactful projects
• Partner with multi-discipline digital teams (data analysts, data engineers, data scientists, and business product owners) to advance data analytics tools/features (such as predictive/prescriptive algorithms and machine learning)
• Ability to deliver work and provide positive leadership in a fast-paced, multi-project team-oriented environment
• Intellectual curiosity with ability to learn new concepts/frameworks, algorithms and technology rapidly as needs arise
• Ability to manage multiple competing priorities simultaneously
• Ability to work in highly collaborative, cross-functional environments

One phone and one virtual panel interview.

We invite qualified candidates to send your resume to  If you decide that you’re not interested in pursuing this particular position, please feel free to take a look at the other positions on our website  You are also welcome to share this opportunity with anyone you think might be interested in applying for this role.