Data Modeller / Engineer II

Airswift is seeking Data Modeler/Engineer II for an initial 6 months to support a major O&G client. Location: Houston, TX Contract Duration: 6 months with the possibility of extension Schedule: 5/40 – On-site The Trading Data Analytics discipline within the Trading Analytics & Insights (TA&I) organization comprises Quantitative Analysts, Data Strategists, and Core Strategists (software engineers). Linked by the common themes of data, numerical algorithms, and technology, the discipline seeks to add value to the business by delivering new models, tradable insights, and agile technology solutions that empower the analyst community and enhance commercial outcomes. This role would be working alongside Gas and Power Trading Americas Fundamental Modelling and Innovation Team. This role provides the opportunity to work closely with analysts and strategists across north American region and commodity lines to design and build scalable solutions to business-critical problems in a fast-paced, data-rich trading environment. Required: STEM Degree Essential Experience • Undergraduate degree in STEM subject or quantitative discipline. • 3-5 years hands-on experience working with machine learning models and regressions. • Excellent python skills with a robust understanding of core data science packages (e.g., pandas, numpy, sklearn, etc.). • Experience manipulating and analyzing large, complex datasets. • Strong attention to detail. • Excellent problem-solving skills. • Track record of working with traders or other business stakeholders to create commercially actionable models. • Independent, creative thinker that can find alternative solutions to complex problems. • Desire to continually improve with a passion to innovate and the ability to develop new analytical methodologies. • Ability and desire to work in a fast-paced, dynamic trading environment. Desirable Experience & Skills • Knowledge of US or North American energy markets (e.g., low-carbon, oil, gas, LNG, or power). • Understanding of supply and demand drivers together with how physical and related financial instruments are traded.