Job Summary

Collaborating closely with members of the analytics team and key subject matter experts across business units, the Data Science Lead identifies opportunities and creates solutions using advanced analytics techniques and tools. The individual is tasked with extracting insights from vast amounts of structured and unstructured data to address specific business needs and goals. In the evolving landscape where businesses increasingly rely on data analytics for decision-making, the role of the Data Science Lead at PIP is crucial, with a focus on leveraging automation and machine learning as integral components of the IT strategies.

Job Responsibilities

Define the vision, strategy, and principles for advanced analytics in collaboration with senior executives to support organizational strategies and priorities.
Lead and manage teams in executing data-related projects, ensuring alignment with organizational goals and priorities.
Collaborate with data architects, ETL developers, Business Intelligence analysts/developers, and subject matter experts to understand company needs and propose solutions.
Stay up to date with the latest technology trends.
Communicate results and ideas to key decision-makers.
Research and develop statistical learning models for data analysis.
Implement new statistical or mathematical methodologies as needed for specific models or analyses.
Collaborate with the Data Engineering team in establishing standards for naming, describing, governing, managing, modeling, cleansing, enriching, transforming, moving, storing, searching, and delivering data within the enterprise.
Understand how data is or will be used, considering implications on people, processes, products, and technology.
Deliver well-defined data design documentation and data models that guide and inform project software development teams.
Define performance and scalability requirements, validating them through performance and scalability testing.
Review advanced analytics business cases and initiatives to identify, assess, and communicate feasibility, architecture requirements, costs, and issues. Provide overall thought leadership to evolving advanced analytics activities.

Core Skills/Competency Requirements

Knowledge and Experience

Experience leveraging the Azure platform and tools such as Synapse and Machine Learning
Extensive background in data mining and statistical analysis
Able to understand various data structures and common methods in data transformation
Excellent pattern recognition and predictive modeling skills
Experience with programming languages such as R/Python
Knowledge of Enterprise Architecture principles, methods, and tools; understanding of data management
Knowledge of master data management and data governance
Ability to understand how the data relates to the current operations and the effects that any future process changes will have on the use of data in the organization

Personal Attributes

Deep understanding of the value of organizational data
Work extremely well with all levels in the organizations
Ability to communicate to executives
Well respected and influential
Able to emphasize methodology, modeling, and governance
Passion for learning

Protective Industrial Products (PIP) is an equal opportunity employer that is committed to diversity and inclusion in the

workplace. We prohibit discrimination and harassment of any kind based on race, color, sex, religion, sexual orientation,

national origin, disability, genetic information, pregnancy, or any other protected characteristic as outlined by federal, state, or local laws.

This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination,

layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. PIP makes hiring decisions based

solely on qualifications, merit, and business needs at the time. For more information, you may request access to our EEO policy.

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Data Science Lead