Data Analyst

Schweitzer Engineering Laboratories•Pullman, WA

About The Position

This role is for a Data Analyst who will be responsible for analyzing data using established statistical methods to deliver accurate, actionable, and timely results. The analyst will maintain and improve indicators and metrics, utilize and enhance existing data sources, and research alternative data sources to improve integrity and reporting. Key responsibilities include reviewing, validating, and cleaning data, resolving data inconsistencies, and developing methods to prevent data inconsistencies at the point of entry. The role also involves collaborating with data owners for system improvements and adhering to SEL Values, Principles of Operations, and World Class Manufacturing Principles. The company emphasizes a culture of 'Understand. Create. Simplify.' and may assign other duties as needed.

Requirements

Related technical BS degree in Math, Statistics, Social Science, or related experience
2+ years of experience
Strong knowledge of MS Word, MS Excel, and MS Access
Strong analytical, judgment, organizational, and project management skills
Strong attention to detail
Strong writing, documentation, and speaking skills
Ability to learn and communicate technical/scientific information
Ability to work independently as well as cooperatively in a team environment
Ability to learn new skills and assume new responsibilities
Background check results satisfactory to SEL
Negative drug test result(s)

Nice To Haves

Experience applying statistical skills in two of the following environments: manufacturing, electronics design or business

Responsibilities

Analyze data using established statistical methods and deliver accurate, actionable, and timely results.
Maintain and improve indicators and metrics.
Use and improve established data sources, research alternative data sources when needed. Understand how additional data sources improve integrity and reporting.
Review, validate, and clean data; resolve and mitigate data inconsistencies.
Develop methods to avoid data inconsistencies at the point of data entry.
Collaborate with data owners to make system improvements.
Follow and apply SEL Values, Principles of Operations, and World Class Manufacturing Principles.
Understand. Create. Simplify.
Other duties as assigned.