Data Analyst, Plant

About

The Dover Wipes Plant Data Analyst Role will be integral to empowering the business to win with consumers. You will be a primary driver of delivering insights that will educate and influence key business decision-making that supports supply chain efficiency, productivity, simplification, and most importantly operational excellence helping to eliminate chronic losses. Additionally, this role will support Product Supply Cybersecurity functions at the site.

Responsibilities

• Lead and improve analytical programs and present the results of your business unit/category/region to leaders.
• Analyze the variable, granular data of your business and regularly use advanced models to deliver business insights across diverse business domains.
• With a combination of analytical expertise, data and system knowledge, and business insight, you’ll answer and anticipate critical business questions and opportunities and deliver insights to the business in ways that make significant impacts.
• Demonstrate use of data visualization (Tableau, Power BI, Excel), and analytic tools (Python, R, SQL, KNIME/Alteryx) to grasp the business insights.
• Collaborate with multifunctional teams (Marketing, Finance, IT, Sales) to improve key business priorities based on your data-driven insights.

Requirements and Qualifications

Data Engineering

• Is familiar with at least one imperative language (C, C++, Java).
• Is familiar with operating system scripting languages (BAT/CMD/PowerShell, bash, Python).
• Is familiar with database SQL language (TSQL, MySQL, PostgreSQL, Oracle, SAP HANA).
• Is familiar with Networking stack (OSI Levels, TCP/IP, NAT, Firewalls).

Data Science

• Is familiar with at least one data science mixed-paradigm language (Python or R).
• Can independently apply basic statistics to analyze a data set.
• Can independently execute data preparation techniques (filtering, imputation, interpolation, resampling, dimensionality reduction) and identify outliers
• Can independently categorize, examine, compare/contrast key features in each data set.
• Can independently evaluate the optimal machine learning algorithm(s) to be used for a certain data set (classification, regression, clustering).
• Can independently apply machine learning algorithms to a data set.
• Can independently apply correct visualization given data set features to be highlighted.