Data Analyst

Location: Remote (Central or Eastern U.S.)

Compensation: $75,000-$85,000 DOE annual base salary + 10% annual target bonus

Visa Sponsorship: Currently, World Fuel is unable to provide current or future employment sponsorship for this position.

Launch Your Analytics Career with World Fuel

Are you passionate about data, technology, and problem-solving? Do you enjoy using analytics to solve real business challenges and influence decision-making?

World Fuel is seeking an early-career Data Analyst to join our Yield and Revenue Management team. This role offers a unique opportunity to work directly with pricing, sales, supply, and trading teams while developing advanced analytical, automation, and business partnership skills.

This position is ideal for recent graduates or early-career professionals with strong technical and quantitative abilities who are looking to apply those skills in a fast-paced commercial environment and who are interested in pricing strategy, profitability analysis, revenue management, forecasting, and commercial decision support.. You will gain exposure to revenue optimization, pricing strategy, machine learning, business analytics, and large-scale data solutions while learning how data drives business performance.

What You’ll Do

• Build and maintain automated data pipelines, analytical tools, and models that support pricing and revenue management decisions
• Analyze large datasets to identify opportunities for margin improvement and revenue growth
• Support pricing, margin, and revenue optimization initiatives through analytical modeling and data analysis
• Create dashboards, reports, and visualizations using Tableau and Power BI
• Write and optimize SQL queries to extract, transform, and analyze business data
• Assist in automating recurring reporting and analytical processes
• Validate and reconcile data across multiple systems to ensure data integrity
• Present analytical findings and recommendations to business stakeholders
• Support acquisition integrations and ongoing revenue management initiatives
• Partner with commercial, pricing, and operational teams to improve performance through data-driven insights

What You’ll Bring

Education

Bachelor’s or Master’s degree in:

• Computer Science
• Data Analytics
• Management Information Systems
• Economics
• Engineering
• Operations Research
• Mathematics
• Applied Mathematics
• Statistics
• Or a related quantitative field

Experience

• Internship, co-op, research, or academic project experience involving data analysis, programming, modeling, or business analytics
• 6 months to 1 years of relevant professional experience in analytics, data science, business analytics, pricing, revenue management, or a related quantitative field preferred
• Demonstrated ability to work with data, solve problems, and communicate findings effectively

Technical Skills

Required

• SQL
• Python
• Strong analytical and quantitative problem-solving skills
• Experience analyzing structured data to answer business questions and develop insights.

Preferred

• Tableau or Power BI
• Alteryx or similar ETL tools
• Experience building dashboards, reports, or analytical models
• Exposure to machine learning, predictive analytics, or optimization techniques through coursework, projects, internships, or professional experience
• Experience developing forecasting models and analyses to support pricing, demand, and commercial planning decisions.

What Will Make You Successful

We’re looking for candidates who:

• Have a strong technical and analytical foundation
• Are naturally curious and enjoy solving complex business problems
• Can translate data into practical recommendations and insights
• Are comfortable communicating with both technical and non-technical audiences
• Demonstrate commercial curiosity and an interest in how businesses make pricing, revenue, and operational decisions
• Want to develop into a trusted business partner who can influence decisions through data-driven insights
• Thrive in fast-paced, collaborative environments
• Are eager to learn and continuously develop new technical and business skills

Preferred Background

Exposure through coursework, internships, co-ops, academic projects, or professional experience in one or more of the following areas is a plus:

• Data analytics or business analytics
• Statistical modeling or machine learning
• Data visualization and reporting
• SQL, Python, or related analytical tools
• Commercial, operational, or financial analysis
• Pricing, revenue management, logistics, or supply chain analytics