DATA ANALYST-WORK FROM HOME

Burjline Builders•Los Angeles, CA

5d•$45 - $55•Remote

About The Position

Universal Logistics Inc., a leading provider of customised transportation and logistics solutions, is seeking a meticulous and analytical Data Analyst to join our dynamic team. This is a fantastic opportunity for a talented individual to work remotely, turning complex data into actionable insights that drive our business forward. The successful candidate will play a crucial role in analysing supply chain data, identifying trends, and helping to optimise our logistics operations across North America.

Requirements

Proven experience as a Data Analyst or Business Data Analyst.
Strong knowledge of and experience with reporting packages, databases (SQL), and programming is highly desirable.
Technical expertise regarding data models, database design, data mining, and segmentation techniques.
Proficiency in statistics and experience using statistical packages for analysing datasets (e.g., Excel, SPSS, SAS).
Strong analytical skills with the ability to collect, organise, analyse, and disseminate significant amounts of information with excellent attention to detail and accuracy.
Adept at queries, report writing, and presenting findings in a clear and concise manner.
A Bachelor's degree in Mathematics, Economics, Computer Science, Information Management, or Statistics is preferred.

Nice To Haves

Previous experience in the logistics or transportation industry would be a significant advantage.

Responsibilities

Interpret data and analyse results using statistical techniques to provide ongoing business reports.
Develop and implement databases, data collection systems, and data analytics strategies that optimise statistical efficiency and quality.
Acquire data from primary and secondary sources and maintain the integrity of our data systems.
Identify, analyse, and interpret trends or patterns in complex data sets related to transportation, supply chain, and contract logistics.
Filter and 'clean' data by reviewing reports and performance indicators to locate and correct problems.
Collaborate with management and operational teams to understand and prioritise business and information needs.
Create informative data visualisations, dashboards, and reports to communicate findings to key stakeholders.
Identify opportunities for process improvements and cost reductions based on data-driven insights.