Data Scientist

Founded over 35 years ago, First Quality is a family‑owned company that has grown from a small business in McElhattan, Pennsylvania into a group of companies, employing over 5,000 team members, while maintaining our family values and entrepreneurial spirit. With corporate offices in New York and Pennsylvania and 8 manufacturing campuses across the U.S. and Canada, the companies within the First Quality group produce high‑quality personal care and household products for large retailers and healthcare organizations.

Our personal care and household product portfolio includes baby diapers, wipes, feminine pads, paper towels, bath tissue, adult incontinence products, laundry detergents, fabric finishers, and dishwash solutions. In addition, we manufacture certain raw materials and components used in the manufacturing of these products, including flexible print and packaging solutions. Guided by our values of humility, unity, and integrity, we leverage advanced technology and innovation to drive growth and create new opportunities.

At First Quality, you’ll find a collaborative environment focused on continuous learning, professional development, and our mission to Make Things Better.

• Work closely with domain experts and SME’s to understand the business problem or opportunity and assess the potential of machine learning to enable accelerated performance improvements.
• Design, build, tune, and deploy divisional AI/ML tools that meet the agreed upon functional and non‑functional requirements within the framework established by the Enterprise IT and IS departments.
• Perform large scale experimentation to identify hidden relationships between different data sets and engineer new features.
• Communicate model performance, results & tradeoffs to stakeholders.
• Determine requirements that will be used to train and evolve deep learning models and algorithms.
• Visualize information and develop engaging dashboards on the results of data analysis.
• Build reports and advanced dashboards to tell stories with the data.
• Lead, develop and deliver divisional strategies to demonstrate the: what, why and how of delivering AI/ML business outcomes.
• Build and deploy divisional AI strategy and roadmaps that enable long‑term success for the organization aligned with the Enterprise AI strategy.
• Proactively mine data to identify trends and patterns and generate insights for business units and management.
• Mentor other stakeholders to grow in their expertise, particularly in AI/ML, and taking an active leadership role in divisional executive forums.
• Work collaboratively with the business to maximize the probability of success of AI projects and initiatives.
• Identify technical areas for improvement and present detailed business cases for improvements or new areas of opportunities.

• PhD or master’s degree in Statistics, Mathematics, Computer Science or other relevant discipline.
• 5+ years of experience using large scale data to solve problems and answer questions.
• Prior experience in the Manufacturing Industry.

• Experience in building and deploying predictive models and scalable data pipelines.
• Demonstrable experience with common data science toolkits, such as Python, PySpark, R, Weka, Num Py, Pandas, scikit-learn, Spa Cy/Gensim/NLTK, etc.
• Knowledge of data warehousing concepts like ETL, dimensional modeling, and semantic/reporting layer design.
• Knowledge of emerging technologies such as columnar and No
  
  SQL databases, predictive analytics, and unstructured data.
• Fluency in data science, analytics tools, and a selection of machine learning methods – Clustering, Regression, Decision Trees, Time Series Analysis, Natural Language Processing.
• Strong problem solving and decision‑making skills.
• Ability to explain deep technical information to non‑technical parties.
• Demonstrated growth mindset, enthusiastic about learning new technologies quickly and applying the gained knowledge to address business problems.
• Strong understanding of data governance/management concepts and practices.
• Strong background in systems development, including an understanding of project…