Fuel Pricing Data Scientist Intern

About the Role

This is an eleven (11) week paid internship program focused on supporting the development, testing, and monitoring of machine learning models for data-driven fuel pricing decisions. The role offers hands-on experience with real-world time-series data, pricing systems, and enterprise ML platforms, working closely with Senior and Lead Data Scientists.

Key Responsibilities

• Support the development and testing of machine learning models used for dynamic fuel pricing.
• Assist with time-series forecasting workflows (e.g., demand, price movement, or market response modeling).
• Perform data cleaning, feature engineering, and exploratory data analysis on large pricing and market datasets.
• Write Python and SQL code to support modeling, analytics, and data pipelines in environments such as Databricks.
• Help validate model outputs through back-testing, diagnostics, and performance tracking.
• Contribute to documentation of models, assumptions, and experimental results.
• Partner with senior team members on pricing experiments, model monitoring, and business analysis.
• Present findings and insights to technical and non-technical stakeholders.
• Learn and apply emerging AI tools (e.g., automation, LLMs) to support modeling workflows.

Requirements & Tech Stack

• Currently pursuing a Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• Coursework or hands-on experience in:
• Python programming
• LLM Experience
• Statistics or Machine Learning
• SQL and data analysis
• Strong analytical thinking and problem-solving skills.
• Ability to work with large datasets and learn complex business processes.
• Clear communication skills and willingness to collaborate across teams.

Preferred Qualifications

• Exposure to time-series forecasting, predictive modeling, or optimization.
• Familiarity with tools such as:
• Pandas, NumPy, scikit-learn
• Spark or Databricks
• Git for version control
• Interest in pricing, economics, retail analytics, or energy markets.
• Prior internship, research, or project experience in data science or analytics.