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Senior Data Scientist AI & Machine Learning - Manufacturing Systems
Senior Data Scientist AI & Machine Learning - Manufacturing Systems-September 2024
Valhalla
Sep 20, 2024
ABOUT PEPSICO
Headquartered in Purchase, NY, PepsiCo is the global leader in food and beverages and operates in over 200 countries and territories around the world.
10,000+ employees
Consumer Goods & Services, Food & Beverage
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About Senior Data Scientist AI & Machine Learning - Manufacturing Systems

  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 analyticsApplication 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 optimizationExperience 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

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