Musket Corp is looking to develop and deploy advanced AI and machine learning solutions to enhance trading performance, market analysis, and operational efficiency in the energy trade floor, specifically in refined products.
Requirements
- Proficiency in Python and experience with core ML frameworks (TensorFlow, PyTorch, scikit-learn).
- Working knowledge of at least one or more of the following: SQL, programming languages such as Java, C-Sharp, or C++.
- Experience integrating data from market feeds, trade capture systems, or time-series databases is a plus
- Expertise in machine learning model development, optimization, and deployment.
- Strong command of Python and data analysis libraries (NumPy, Pandas, SciPy).
- Experience with big data platforms and cloud-based environments (AWS, Azure, Snowflake).
- Ability to develop end-to-end solutions—from data ingestion to insight visualization—tailored to trading needs.
Responsibilities
- Build and deploy machine learning models that support refined product trading decisions, such as price forecasting, flow prediction, arbitrage detection, and margin optimization.
- Mine, clean, and analyze large datasets from diverse trading sources—market data feeds, vessel tracking, logistics, and inventory systems—to identify actionable patterns and insights.
- Apply advanced statistical and AI methods (supervised/unsupervised learning, NLP, computer vision) to improve market understanding and risk management.
- Write clean, efficient, and production-ready code for model deployment, data pipelines, and algorithmic trading tools.
- Design and implement scalable data science frameworks that integrate with trading systems, databases, and visualization platforms.
- Continuously monitor, evaluate, and refine model performance to ensure reliability and alignment with changing market conditions.
- Stay ahead of emerging AI trends, open-source tools, and advanced analytics techniques relevant to commodities and financial trading.
Other
- Bachelor’s degree in Computer Science, Data Science, Engineering, Applied Mathematics, or a related quantitative field required.
- Graduate degree (Master’s or PhD) in AI, Machine Learning, or a related technical discipline is a plus
- Proven experience applying AI and machine learning techniques to solve real-world commercial or financial problems.
- Exposure to or interest in energy trading, refined products, or commodity analytics strongly preferred
- Collaborative, proactive, and results-oriented with excellent communication skills.
