Data Analyst - Energy Sector (Remote)

About the Role

Our client is looking for a skilled Data Analyst to join their remote team, focusing on the energy sector . In this role, you will be instrumental in collecting, processing, and analyzing large datasets to provide actionable insights that drive business decisions and operational improvements. You will work closely with various departments, including operations, engineering, and finance, to identify trends, forecast performance, and report on key metrics. This is an exciting opportunity for a data-savvy professional to make a significant impact from anywhere, contributing to the strategic direction of the company in a remote-first environment.

Key Responsibilities

• Collect, clean, and organize large datasets from various sources within the energy industry.
• Perform statistical analysis to identify trends, patterns, and correlations in operational and financial data.
• Develop and maintain dashboards and reports to visualize key performance indicators (KPIs).
• Collaborate with stakeholders to understand their data needs and provide analytical support.
• Utilize data mining techniques to extract valuable business insights and make recommendations.
• Ensure data integrity and accuracy throughout the analysis process.

Requirements

• Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
• Minimum of 3 years of experience as a Data Analyst , preferably within the energy sector.
• Proficiency in data analysis tools and languages such as SQL, Python (Pandas, NumPy), or R.
• Experience with data visualization tools like Tableau, Power BI, or similar.
• Strong understanding of statistical concepts and methods.
• Excellent problem-solving skills and ability to communicate complex findings clearly.

Benefits

• Competitive salary and performance-based incentives.
• Fully remote work arrangement with flexible hours.
• Comprehensive medical, dental, and vision insurance.
• Opportunities for professional development and continuous learning in data science.
• A collaborative and supportive virtual team environment.