Job Summary Immediate opportunity for a Data Scientist with a strong engineering foundation, preferably in Mechanical, Biomedical, or Chemical Engineering, who will apply their expertise in in-silico modeling, simulation, and data analysis to support combination product development. This role supports the Combination Product Predictive Modeling & Enabled Insights organization and focuses on building and managing digital modeling assets, applying simulation techniques to physical systems, and leveraging data insights to inform decisions. The Digital Data Scientist will support the way Company 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. Schedule: Hybrid schedule based in Thousand Oaks, CA, with an expectation of onsite presence at least 3 days per week. Candidates must be able to commute regularly to the Thousand Oaks site and collaborate effectively in both onsite and remote settings. Key Skills • Programming in Python, MATLAB, JMP, and/or Minitab for engineering purposes • Model simulation and analysis (MS&A) techniques for structural, fluidic, and heat transfer problems using commercial software such as ANSYS, LS-Dyna, ABAQUS, COMSOL • Mathematical / first principles modeling, numerical techniques, and uncertainty quantification such as Monte Carlo simulations • Applying simulation techniques to physical system location: Newbury Park, California job type: Contract salary: $50.00 - 57.20 per hour work hours: 9 to 5 education: Bachelors Responsibilities 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 mechanical and biomedical 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. Qualifications • Bachelor's degree (BS) in Engineering plus 5 years of simulation, modeling, and data analysis experience OR • Master's degree (MS) in Science or Engineering plus 2 years of simulation, modeling, and data analysis experience OR • Ph.D. in Science or Engineering (simulation, modeling, and data analysis) 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 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 • Familiar with utilizing GitLab 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 Preferred Traits • 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 skills: Statistical Programming, Biomedical Engineering, Mechanical Engineering, Medical Device Product Development Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status. At Randstad, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact HRsupport@randstadusa.com. Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad offers a comprehensive benefits package, including: medical, prescription, dental, vision, AD&D, and life insurance offerings, short-term disability, and a 401K plan (all benefits are based on eligibility). This posting is open for thirty (30) days. Qualified applicants in San Francisco with criminal histories will be considered for employment in accordance with the San Francisco Fair Chance Ordinance. Qualified applicants in the unincorporated areas of Los Angeles County with criminal histories will be considered for employment in accordance with the Los Angeles County's Fair Chance Ordinance for Employers. We will consider for employment all qualified Applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance. u00006475229