Accounting Data Scientist

Mercuria is one of the world’s leading independent energy and commodity groups. Our purpose is to connect markets and to advance the energy transition. We bring markets together to support the world’s energy needs of today by trading, structuring finance, and investing in strategic assets, whilst generating over $170 billion in turnover. We are committed to advancing the transition to a more sustainable, affordable, and reliable energy system for tomorrow. We are well ahead of the pledge we made in 2021 that over half of our investment capital will go into sectors that are advancing the energy transition by 2025, to contribute to global efforts to combat climate change.

We are seeking an innovative and detail-oriented Accounting Data Scientist to join our dynamic team. The ideal candidate will have a strong background in data science and accounting, with a focus on developing and implementing advanced models to enhance financial operations. This role involves leveraging cutting-edge technologies, such as Optical Character Recognition (OCR) and Large Language Models (LLM), to improve fraud detection, automate data extraction, and streamline financial processes.

Role and Responsibilities:

Fraud Detection and Error Prevention in Payments:

• Develop and maintain an advanced OCR-LLM model for the accounting team.
• Utilize state-of-the-art Generative AI algorithms to enhance historical pattern recognition models.
• Extract and analyze data from physical invoices, comparing classifications to manual entries to detect fraudulent invoices and discrepancies.
• Safeguard company finances by significantly reducing the risk of erroneous payments.
• Collaborate on larger projects utilizing similar techniques to support other departments, such as Settlements.

Automation of Invoice and Bank Details Extraction:

• Engineer models for the Accounts Payable team to autonomously retrieve and process counterparty invoices and bank details from shared financial document repositories.
• Streamline data management and enhance the accuracy and efficiency of data retrieval for financial operations.

Enhanced Financial Reconciliation:

• Improve existing financial reconciliation models by integrating functionalities such as handling partial payments and adding new clearing scenarios.
• Generate region-specific reports for Mercuria bank reconciliation teams to support precise reconciliations and informed decision-making.

Automation of Accounting Closing Tasks:

• Create models that automate the signoff process for accounting closing tasks.
• Verify balance matches, document postings, and general ledger entries to reduce manual workload and ensure compliance.
• Accelerate the financial closing process through automation.

Mentorship:

• Provide guidance to external interns focused on refining the OCR-LLM model.
• Develop additional capabilities, such as multiple data extractions from physical invoices, to enhance model performance.

Skills and Competencies:

• Master’s degree in data science, Computer Science, Accounting, Finance, or a related field with a strong analytical focus.
• Extensive experience in developing and implementing Optical Character Recognition (OCR) and Large Language Models (LLM) specifically for financial applications.
• Proficiency in programming languages such as Python, R, or Java, with a focus on data manipulation and machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of Generative AI algorithms and their application in fraud detection and error prevention.
• In-depth knowledge of accounting principles and financial reconciliation processes.
• Experience in automating financial tasks, such as invoice processing and bank detail extraction, to enhance operational efficiency.
• Proven ability to analyze complex datasets and extract meaningful insights to support financial decision-making.
• Experience in developing models that handle partial payments, new clearing scenarios, and generate region-specific financial reports.
• Demonstrated ability to manage projects from conception to implementation, ensuring alignment with business objectives and timelines.
• Experience in collaborating with cross-functional teams to enhance model capabilities and support broader organizational goals.
• Experience in mentoring junior team members or interns, particularly in refining and expanding the capabilities of data science models.
• Ability to provide technical guidance and support to enhance team performance and model accuracy.
• Experience in documenting model development processes and outcomes for audit and compliance purposes.
• Fluent in English