Sr. Specialist - Data Analytics

Job Summary

It is recognised that the size and complexity of Shell Trading & Supply (T&S) has increased substantially over the past few years and the expectations around risk management from a regulatory perspective have also shifted for Energy Trading. As a result, and also recognising the potential to unlock additional value from enhanced risk management of our trading activities, a strategic decision has been made to make a major investment over the next 3-4 years to strengthen the risk management capabilities of the organisation from a people, process, data and systems perspective in both the first and second lines of defence.

Sr. Specialist - Data Analytics team within Credit focuses on the delivery of regular and ad hoc credit risk reporting and portfolio analytics to the commercial teams, the risk management teams and various other stakeholders such as the TSLT, EC and the production of risk information which will flow into external financial reporting.

This role relates to Trading & Supply (T&S). Primary stakeholders are commercial teams, credit risk managers located in T&S hubs of London, Houston, Rotterdam, Dubai and Singapore. The role is focused on providing support for credit reporting and analytics activities globally.

What you will be doing

• Support the development and operations of global credit risk reporting activities within T&S, including working with IT and other organisations to resolve issues where they arise.
• Develop and conduct credit risk analytics on both a pre- and post-deal basis; including, but not limited to, Potential Future Exposure (PFE), portfolio analytics, expected credit loss (ECL), credit value adjustment (CVA), credit reserves and cost of credit analysis.
• Combine business understanding with logical data modelling and process design skills to integrate new T&S businesses and enhanced activities into global operations.
• Ensure reporting and analytical tools have clear and appropriate documentation and controls.
• Develop and enhance appropriate data visualisations to support the use of credit reporting and analytics - e.g. Spotfire, Power BI and/or other visualisation tools.
• Understand the key ETRMs of T&S, with in-depth knowledge of how systems in their region interact with Risk systems and tools.
• Train users on how to conduct analysis in tools developed and supported by Risk.
• Provide support and direction to Risk colleagues.
• Collaborate with and support Commercial / Credit / Market Risk / Valuation teams with production reporting, transformation projects and other ad-hoc requests.

What you bring

• Hands on experience on analytics projects
• At least 5 years of relevant working experience
• Practical experience applying AI/ML techniques in an analytical or risk context - including predictive modelling, classification, anomaly detection, or NLP.
• Strong Python skills for data analysis and automation, with working knowledge of machine learning frameworks (e.g. scikit-learn, XGBoost, statsmodels) and data science libraries (pandas, numpy, scipy)
• Experience with database programming languages, data engineering and data transformation.
• Excellent attention to detail, methodical, organized and able to plan to meet deadlines.
• Resilient when working under pressure, with the ability to prioritise tasks to meet deadlines
• Self-starter, highly motivated, outcome driven.
• Good judgement to provide advice, question discrepancies, escalate issues.
• Learner mindset: innovative and creative, excellent problem-solving capabilities including the ability to analyse, model and interpret data.
• Strong interpersonal and team working skills in order to communicate with various different stakeholders across Risk, IT and Commercial, all with varying needs.
• Knowledge of Apache Airflow, Azure Data Factory, or equivalent orchestration tools for pipeline automation would be preferred.
• Exposure to Azure Data Mesh architecture, data product thinking, or MLOps practices would be preferred.
• Experience in data visualisation - Power BI, Spotfire, QlikSense or other, would be preferred.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.