Data Scientist

About the job

Overview

Pactiv Evergreen Inc. (NASDAQ: PTVE) is a leading manufacturer and distributor of fresh foodservice and food merchandising products and fresh beverage cartons in North America and certain international markets. It supplies its products to a broad and diversified mix of companies, including full service restaurants and quick service restaurants, foodservice distributors, supermarkets, grocery and healthy eating retailers, other food stores, food and beverage producers, food packers and food processors. To learn more about the company, please go to the company website at pactivevergreen.com.

Pactiv Evergreen is committed to a diverse and inclusive workforce. Pactiv Evergreen is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, sex (including pregnancy), sexual orientation, religion, creed, age national origin, physical or mental disability, genetic information, gender identity and/or expression, marital status, veteran status or other characteristics or statuses protected by law. For individuals with disabilities who would like to request an accommodation, please call (847) 482-4320 or email TalentHelp@Pactiv.com .

All information will be kept confidential according to EEO guidelines and applicable laws.

Responsibilities

Data Scientist

Responsible for generating data insights and identifying and validating innovation opportunities. This position is part of Pactiv’s digital manufacturing transformation by implementing, supporting, and continuously optimizing digital manufacturing solutions to improve overall OEE and reduce cost. It will partner with the plants by providing services needed to conduct deployment assessments, surface innovation opportunities, and continuously innovate digital manufacturing capabilities.

This position is for Pactiv Evergreen.

Responsibilities

  • Mine, process, and analyze data from multiple sources to identify meaningful relationships, patterns, or trends from complex data sets
  • Define problems to be solved and apply advanced data science methods including machine learning algorithms, to discover opportunities to increase OEE, reduce cost per pound or provide insights to plants on process disruptions
  • Maintain and tune analytical models to predict and monitor the condition of plant assets and people.
  • Prepare data insights in narrative or visual forms, e.g., dashboards for stakeholder review or decision making, etc.
  • Implement and maintain data standards, data processes, and new analytics capabilities to continuously enhance asset intelligence
  • Ability to travel occasionally (10-30% – depending on location) to work with Solutions Manager and the plants as required.

Experience

Qualifications

  • BS/MS Computer Science and/or Engineering
  • 1 – 3 years of experience in the design and implementation of data infrastructures and data hierarchies
  • 1 – 3 of years of experience in data model development, data visualization, and application of advanced analytics to drive business outcomes
  • Background in operations research or related field, e.g., Industrial Engineering, and manufacturing experience preferred

Key Past Experience

  • Using Python or R programming languages
  • Maintaining data storage and/or architecting databases for ease of use
  • Using analytics models and different algorithms to solve business problems / achieve specific business benefits
  • Hands-on experience in data visualization (e.g, dashboards) and use of tools (e.g., Tableau, Qlikview) to articulate complex concepts simply to a broad audience (users, technical and functional teams, and senior management)
  • Knowledge of statistical analysis methods (e.g., t testing, regression) and tools (e.g., R)

Skills & Attributes

  • Proficiency with statistical analysis methods and tools, e.g., Python or R
  • Ability to utilize data to identify problems and translate to provide solutions
  • Knowledge of machine learning disciplines and algorithms
  • Understanding of process areas (leadership/supervision, process, maintenance)

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