• Application Deadline:
• Position: Data Analyst



• Job Type Full Time



• Qualification BA/BSc/HND



• Experience 4 years



• Location Lagos




• Job Field Data, Business Analysis and AI 
  
  

Job Summary

• We are seeking a highly analytical and detail-oriented Data Analyst to join our team in the oil and gas sector.


• The ideal candidate will be responsible for collecting, processing, and analyzing complex datasets to support data-driven decision-making. 


• This role requires strong data visualization skills, statistical analysis capabilities, and industry-specific knowledge to optimize operations and business performance.

Key Responsibilities

• Collect, clean, and analyze large datasets related to production, operations, and market trends in the oil and gas sector.


• Develop and maintain dashboards, reports, and data models to support business intelligence and strategic planning.


• Provide insights and recommendations based on data analysis to improve efficiency and reduce costs.


• Work closely with engineering, finance, and operations teams to identify data needs and drive analytical solutions.


• Utilize predictive analytics and machine learning models to forecast trends and enhance decision-making.


• Ensure data integrity, accuracy, and compliance with industry regulations.


• Present findings to management and stakeholders through clear reports and visualizations.

Qualifications & Experience

• Bachelor’s degree in Data Science, Statistics, Engineering, Computer Science, or a related field.


• Minimum of 4 years of experience in data analysis, preferably in the oil and gas industry.


• Proficiency in SQL, Python, R, or other data analysis tools.


• Strong experience with data visualization tools such as Power BI, Tableau, or similar.


• Knowledge of oil and gas industry metrics, production data, and market trends.


• Experience in working with large datasets and database management.


• Strong problem-solving skills and attention to detail.

Preferred Skills:

• Experience with geospatial data and GIS tools.


• Familiarity with industry-specific software and databases.


• Knowledge of predictive modeling and machine learning techniques.