Data Modeling Analyst, Sr. develops data models to meet the needs of the organization's information systems. Manages the flow of information between departments through the use of relational databases. Being a Data Modeling Analyst, Sr. maintains data integrity by working to eliminate redundancy. Stays informed of the ways the organization uses its data. Additionally, Data Modeling Analyst, Sr. requires a bachelor's degree. Typically reports to a manager. To be a Data Modeling Analyst, Sr. typically requires 4 to 7 years of related experience. Contributes to moderately complex aspects of a project. Work is generally independent and collaborative in nature. (Copyright 2024 Salary.com)
Job Description
-- Will be responsible for analyzing, collecting, and monitoring data on a recurring and ad hoc basis.
-- Will develop new reporting to support the Operations.
-- Assisting with operational workflow by timely and accurate loading of data into Operations systems to optimize and maximize the production calls.
-- Tracking overall production performance results and the key resource components, distribute substantive analysis, collaborating directly with Operations staff to evaluate the ongoing effectiveness of operating metrics and measurement methods and continually improve them as needed or directed.
-- Assist in generating reports for Sales and Client Services, evaluate and implement new tools to promote or analyze performance improvement and to contribute to financial reviews, proposals, pricing, and forecasting budget development.
Requirements
--Analytical Skills: Data analysts work with large amounts of data: facts, figures, and number crunching. Need to see through the data and analyze it to find conclusions.
--Communication Skills: Data analysts are often called to present their findings, or translate the data into an understandable document. Need to write and speak clearly, easily communicating complex ideas.
--Critical Thinking: Data analysts must look at the numbers, trends, and data and come to new conclusions based on the findings.
--Attention to Detail: Data is precise. Data analysts have to make sure they are vigilant in their analysis to come to correct conclusions.
--Math Skills: Data analysts need math skills to estimate numerical data
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