Quantitative Data Engineer

INEOS Energy is the energy division of INEOS, we produce and trade oil and gas. Operating across the Danish and UK North Sea with offshore oil & gas assets and onshore assets in South Texas, US. We also have a portfolio of non-operated assets built around two deep water early production assets in the US Gulf. This is supported by our investments in low carbon technologies, which will help sustain our business through the energy transition.INEOS Energy Trading operates as the single face to the Gas, LNG, Power, Carbon, and Crude Oil commodity markets for INEOS. Our core mission is to fully monetise INEOS Energy’s equity Oil and Gas production across Europe and the US.Beyond this, the Trading and Business Development teams are tasked with originating and developing complementary third-party physical business.We also support the wider INEOS group by leveraging our carbon trading capabilities and supplying LNG, Gas, and Power to INEOS’s industrial base.Our team is on an exciting growth journey, and we anticipate continued growth across both new commodities and geographies, as the business evolves to support INEOS Energy’s expanding global footprint.The Quantitative Data Engineer is responsible for developing and maintaining the data infrastructure, platforms and analytical solutions that support trading and commercial decision-making. The role covers data pipelines, Snowflake platform development and optimisation, analytics dashboards, analytical tools and machine learning models, ensuring traders have access to reliable, high-quality data and actionable insights across global crude oil markets.RESPONSIBILITIES & ACCOUNTABILITIESDevelop, maintain and improve data pipelines, and contribute to the development and optimization of the Snowflake data platform.Maintain and enhance analytics dashboards.Develop and deploy new analytical tools and solutions.Perform ad-hoc analysis to support traders, including data cleaning, exploratory analysis, statistical testing and interpretation of results.Document analytical methodologies, models and data processes to support reproducibility and knowledge sharing.Apply machine learning techniques to develop models for components of supply-demand balances across US, European and Asian markets.SKILLS, EXPERIENCE & EDUCATIONProficiency in Python and SQL.Experience working with cloud-based data platforms and/or AWS is a plus.Experience with the end-to-end machine learning lifecycle, including data preparation, feature engineering, model development is a plus.Understanding of crude oil market dynamics and supply-demand fundamentals is a plus.Master’s degree in a quantitative discipline such as Mathematics, Computer Science, Data Science, Statistics, Engineering, or a related field.BEHAVIOURAL SKILLS & PERSONAL ATTRIBUTESStrong collaboration skills, with the ability to work effectively with both technical and non-technical stakeholders.Ability to communicate complex technical concepts and analytical results clearly and concisely.Self-motivated, proactive and able to learn independently.Demonstrates initiative in identifying opportunities for process improvement and developing new analytical ideas and solutions.Strong problem-solving skills and attention to detail.Notice To Third Party AgenciesINEOS does not accept unsolicited CVs from recruiters, employment agencies, or other staffing services. Unsolicited CVs include any resume or hiring document sent to INEOS in the absence of a signed Service Agreement where INEOS has expressly requested recruitment/staffing services specific to the position at hand. Any unsolicited CVs, including those submitted to hiring managers or other business leaders, will become the property of INEOS and INEOS will have the right to hire that candidate without reservation - no fee or other compensation will be owed or paid to the recruiter, employment agency, or other staffing service.