Data Scientist

LHP Engineering Resource Division

We are looking for a passionate, creative individual that is able to turn data into information, information into insight and insight into product directions, customer guidance and business decisions. You will conduct full lifecycle activities to include requirements analysis and design, development, and continuously monitor performance and identify improvements. You will interact directly with customers and users of your work. This role can make a major impact to all areas of our business, especially customer satisfaction, efficiency/productivity and product development.

Manage large amounts of data; merge data sources; ensure consistency of datasets; must be able to handle datasets of multiple types – textual, categorical and numerical

Identify, analyze, and interpret trends or patterns in complex data sets, create predictive models based on those patterns

Filter and clean data, and review computer reports, printouts, and performance indicators to locate and correct code problems

Present and communicate the data insights/findings (preferably actionable insights) to both specialists as well as a non-technical audience

Create visualizations to aid in understanding data

Customer interface and communication skills

A passion for empirical research and answering hard questions with data

Technical expertise regarding data models, database design development, data mining and segmentation techniques

Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy

Strong knowledge of statistics and experience using statistical packages for analyzing large datasets (Minitab, SPSS, SAS, Excel, etc)

Adept at queries, report writing and presenting findings

Knowledge of Lean systems and value stream mapping

Fluent with one or more software development languages (especially C#, “R”)

Experience with web development and agile methodologies and processes

BS/MS in Mathematics, Engineering, Computer Science, Data Science, Informatics or Statistics

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