Analyst - Credit Portfolio Management Trafigura

About Trafigura

Job Description

As a Data Engineer and Data Scientist at our organization, your primary responsibility will be to handle various aspects of data engineering, data science, risk modeling, risk reporting, visualization, data governance, and infrastructure management. You will be required to work closely with internal and external data sources, develop risk models and algorithms for credit scoring, simulate stress scenarios, and create LLM models to support credit risk assessment. Your key responsibilities will include sourcing data from internal and external sources through data pipelines, developing automated data ingestion processes, implementing data quality controls, and monitoring systems to ensure data integrity. You will also be responsible for designing and maintaining sophisticated risk models, building predictive models for credit loss estimation, and creating stress testing scenarios to evaluate portfolio resilience. Furthermore, you will be tasked with developing risk reports, interactive dashboards, and visualization tools for credit risk officers to analyze and monitor risks effectively. Additionally, you will need to organize and document data attributes, processes, and procedures to ensure proper data governance. Collaboration with internal technology teams to analyze the impact of infrastructure changes on data integrity will be a crucial aspect of your role. You will also work closely with key departments across the organization, including Accounting, Trade Finance, Operations, and Deal Desk, to understand data throughout the trade life cycle. To excel in this role, you should hold a Bachelor's degree in computer science, Finance, Mathematics, Statistics, or a related field, along with 3-5 years of experience in data engineering, data science, or a similar technical role. Proficiency in SQL, database management systems, and programming skills in Python, R, or similar languages for statistical analysis and machine learning is essential. Experience with machine learning frameworks, statistical modeling, econometrics, ETL/ELT tools, data visualization tools, Large Language Models, and Natural Language Processing techniques will be advantageous. Strong communication skills in English, both verbal and written, are also required for effective collaboration with various departments and stakeholders across the organization. Key Relationships: - Global Credit team - Risk technology team - Data scientist team - Other internal departments such as accounts, treasury, trade finance, and operations In summary, as a Data Engineer and Data Scientist, you will play a vital role in driving data-driven decision-making processes, enhancing credit risk assessment procedures, and ensuring the overall integrity and effectiveness of our data management practices.,