Senior Data Scientist

fulltime
Expired

Employment Information

The position you were interested in has been filled or expired, but we invite you to explore other exciting job openings on our platform to find your next career opportunity.

Job Description

Overview

PepsiCo’s strategy is to build capabilities that can enable us to become Faster, Stronger, and Better. Packaging can be a critical lever to enable this, by driving better consumer experiences and product liking, bringing cost opportunities to our bottom line, and integrating purpose into our business strategy through sustainable packaging. And more and more we have the need to deliver this right first time, and in the most timely and agile way. To do this effectively, we therefore need to transform the way we work, looking holistically at our end-to-end development processes, from design to market implementation. This will require us to move from more physical development and testing to a virtual development process, using the latest virtual design tools, data analytics, digital models, and prototyping capabilities.

The PepsiCo Global Beverages Packaging R&D Advanced Engineering & Design Team is leading the PepsiCo R&D digital transformation for Beverage Packaging. With the vision of delivering winning products through digital innovation, this team develops breakthrough technologies centered around Modeling and Simulation (M&S), Machine Learning and Artificial Intelligence to deliver faster and better consumer centric innovated packaging and sustainable solutions.

Digital Analysis, AI/ML and Digital Twins, combined with smart, instrumented physical testing can accelerate packaging design, structures, and processes. Working as a team of R&D professionals, you will partner with the R&D Packaging Teams, Data Analytics Teams and Industrial Design Teams to apply advanced tools and capabilities for new package design and development.

Responsibilities

  • Lead development of advanced analysis capabilities, leveraging data science and analytics principles.
  • Combine physics-based simulation, sensor technology, data analytics (AI/ML) to deliver digitized innovation projects (digital twin) in support of key packaging processes.
  • Build and train virtual models based on physical data; design and develop innovative experiments to validate and improve models.
  • Validate virtual and physical sensors, in lab-scale and pilot plant scale process packaging applications.
  • Work with external partners, OEMs, engineering firms, etc., to develop technologies needed to fulfill PepsiCo’s need, while protecting PepsiCo’s information and intellectual property.
  • Travel mainly in North America however some international travel may be required to meet project and business objectives, 10% total travel target.

Qualifications

  • M.S. degree or PhD in Data Science and Data Analytics OR Chemical Engineering, Mechanical Engineering, Material Science & Materials Engineering or similar field
  • Masters candidates require 1+ years of experience in Simulation, Data Science and Analytics, preferably in consumer goods field (preferably in rigid and flexible packaging)
  • PhD candidates require strong research experience in data analytics
  • Application of reduced order surrogate models in industrial applications (AI/ML)
  • Demonstrated expertise on application of data science and analytics principles in industrial applications, to verify performance and manufacturability, and drive form/fit/function optimization
  • Experience with CAD software: SolidWorks, Catia, Creo/ProE, Fusion360
  • Experience with data science and analytics software such as NumPy, SciPy, Matplotlib, TensorFlow, ML, DL, NLP, GCP.
  • Experience with analysis software: Abaqus, LS-Dyna, ANSYS, Fluent, MSC –Nastran, SW Simulation.
  • Fundamental knowledge of numerical methods and physics-based simulation (FEA, DEM, CFD)
  • Solid experience with data science and analytics software and tools, advanced engineering, and simulation preferred.

Preferred Skills:

  • Knowledge and experience in packaging processes – injection molding, stretch blow molding.
  • Understanding of Structural Mechanics, Polymer Material Modeling, Material Characterization, Stress/Strain analysis, Additive Manufacturing.
  • Hands-on experience with commercial software - FEA (ABAQUS, ANSYS Mechanical), DEM (ROCKY, EDEM), CFD (ANSYS FLUENT, STAR-CCM+), COMSOL.
  • Experience with Python, MATLAB, R, JMP (or other statistical software) a plus.
  • Strong project management and communication skills.
  • Ability to collaborate with internal and external partners in a global setup.

Compensation and Benefits:

  • The expected compensation range for this position is between $74,800 - $125,250 based on a full-time schedule.
  • Location, confirmed job-related skills and experience will be considered in setting actual starting salary.
  • Bonus based on performance and eligibility; target payout is 8% of annual salary paid out annually.
  • Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement.
  • In addition to salary, PepsiCo offers a comprehensive benefits package to support our employees and their families, subject to elections and eligibility: Medical, Dental, Vision, Disability, Health and Dependent Care Reimbursement Accounts, Employee Assistance Program (EAP), Insurance (Accident, Group Legal, Life), Defined Contribution Retirement Plan.

EEO Statement

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. PepsiCo is an Equal Opportunity Employer: Female / Minority / Disability / Protected Veteran / Sexual Orientation / Gender Identity If you'd like more information about your EEO rights as an applicant under the law, please download the available EEO is the Law & EEO is the Law Supplement documents. View PepsiCo EEO Policy. Please view our Pay Transparency Statement

joxBox

Join our newsletter to get monthly updates on data science jobs.

joxBox