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2 months ago

Job Summary

The main purpose of this role is to turn raw data into actionable insights that drive better decision-making by turning numbers to word interpretations.

  • Minimum Qualification: Bachelors
  • Experience Level: Mid level
  • Experience Length: 2 years

Job Description/Requirements

JOB TITLE: DATA ANALYST

JOB PURPOSE:

The main purpose of this role is to turn raw data into actionable insights that drive better decision-making by turning numbers to word interpretations. 


COMPANY BACKGROUND:

We at Fabrication Systems (U) Ltd deal in Structural fabrication, Aluminum & Glass, General metal fabrication, signage, and Civil & Turnkey works which form a major part of our product list.

FSUL is the exclusive distributor for Otis Lifts, Ace Equipment, Greaves Generators, Jindal & Servotec stabilizers, Indoair Compressors and Safex Over Head Cranes in East Africa and has a partnership with Bohler Welding to supply the Ugandan market with high-quality welding consumables.



Duty Station:  Head Office

Job Type:  Full Time

Reporting to: HR


RESPONSIBILITIES

  • Data collection from various databases, spreadsheets, and external data feeds. Ensure   that the data is accurate, complete, and up-to-date.
  • Use statistical analysis & data mining to extract meaningful insights from the data. 
  • Create visualizations, such as charts, graphs, and maps, to effectively communicate your findings. 
  • Prepare reports and presentations to share with your in charge. You should be able to communicate complex concepts in a clear and concise manner.
  • Stay up-to-date with the latest trends and techniques in data analysis, as well as new tools and technologies. 


QUALIFICATIONS

  • Diploma/Degree in Business Statistics or any related course.
  • 2-3years Experience (Background in Construction and Factory setting is an added advantage)


SKILLS REQUIRED

  • Programming languages, excellent excel and MS Word.
  • Data wrangling and manipulation
  • Statistical analysis: Hypothesis testing, regression analysis, and machine learning algorithms concepts.
  • Data visualization: Using concise charts, graphs, and dashboards
  • Database management

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