Data Scientist

Job Summary

This isn't about maintaining existing systems - you'll be architecting the analytical foundation that spots major market shifts or dislocations and drives real commercial value. You'll lead the development of sophisticated models and analytical frameworks across natural gas, LNG, power, and related commodities while shaping the data strategy that supports critical trading decisions. The role combines hands-on advanced modeling with strategic thinking about data acquisition and architecture, with the autonomy to steer the ship and move quickly as both you and the business scale up. Reporting structure within Fundamental & Quantitative Analytics team will be determined based on team composition and individual experience levels.

Job Duties & Responsibilities

• Lead end-to-end advanced modeling initiatives from identifying data needs and acquisition strategies (vendor sources, web scraping, internal systems, unstructured data) through to deployment of production models
• Develop and implement sophisticated analytical techniques including machine learning, time series forecasting, optimization models, and statistical analysis to address critical business themes with speed and accuracy
• Serve as the technical visionary for applying novel analytical techniques and emerging technologies including machine learning, artificial intelligence, and large language models to energy commodity challenges
• Collaborate closely with the Lead Data Engineer to develop integrated data strategy that supports both current analytical needs and cutting-edge technological applications
• Collaborate closely with data engineers and analysts to translate complex business requirements into technical data solutions, ensuring seamless integration from data acquisition to model deployment
• Drive rapid response capabilities for market analysis, developing models and insights that can quickly adapt to changing market conditions and emerging opportunities
• Build and maintain advanced analytical outputs including predictive models, risk assessment tools, optimization algorithms, and real-time monitoring systems
• Automate and streamline analytic processes and products
• Establish best practices for modeling processes (e.g. technical documentation, code review, version control, etc.)
• Partner with the Director and analytics team members, traders, and commercial stakeholders to identify high-impact analytical opportunities and translate findings into actionable business intelligence
• Contribute to establishing best practices for model development, validation, and deployment while mentoring junior team members on advanced analytical techniques

Job Specific Skills

• Strong background in machine learning, statistical modeling, optimization, and time series analysis with proven ability to apply these techniques to real-world business problems
• Proficiency with advanced analytical tools including Python/R, SQL, machine learning frameworks (scikit-learn, TensorFlow, PyTorch), and cloud computing platforms
• Experience with diverse data acquisition and integration methods including APIs, web scraping; database management, schema development, and application of metadata layers; and working with both structured and unstructured data sources
• Strong understanding of data architecture principles and ability to contribute to strategic decisions about data storage, processing, and modeling infrastructure, including cloud compute solutions (Snowflake experience preferred but not required)
• Energy commodity market knowledge or demonstrated ability to quickly develop deep domain expertise in complex technical markets
• Excellent communication skills with ability to translate complex analytical concepts into clear business insights for both technical and non-technical stakeholders

Education

Minimum: High school diploma or GED

Preferred: Bachelor’s degree - from accredited university - Mathematics, Statistics, Analytics, Engineer, Computer Science, or related field

Preferred: Master’s degree - from accredited university

Experience

Minimum: 2 - 5 years related work experience

Prior or current data science, quantitative analysis, or related technical roles with demonstrated expertise in advanced modeling techniques

Additional Qualifications

• Natural Gas Market Experience: Experience with natural gas market fundamentals including basis trading, pipeline systems, storage dynamics, and location-specific pricing datasets. Candidates from adjacent markets (power, crude oil, financial commodities) with strong analytical aptitude will be considered
• Energy Trading Background: Experience at energy trading firms, commodity companies, or related commercial energy organizations with understanding of market dynamics and trading applications
• Advanced Technical Skills: Experience with optimization software (Gurobi, CPLEX), advanced time series methods, or specialized domain modeling techniques
• Data Strategy Experience: Track record of contributing to or leading data architecture decisions, platform selection, or analytical infrastructure development
• Cross-Functional Leadership: Experience working across technical and business teams to drive analytical initiatives from conception to implementation
• Real-Time Analytics: Experience developing models and systems that support time-sensitive business decisions or trading applications
• Emerging Technologies: Experience with or strong interest in applying novel technologies including large language models, advanced AI techniques, or cutting-edge analytical methods to business applications