Senior Data Scientist - Risk & Lending - Fintech

Ebury
ES - Madrid - Madrid
November 6, 2024

Ebury is a hyper-growth FinTech firm, named in 2021 as one of the top 15 European Fintechs to work for by AltFi.
We offer a range of products including FX risk management, trade finance, currency accounts, international payments and API integration.
Madrid Office - Hybrid:
4 days in the office, 1 day working from home
Join Our Data Team at Ebury Madrid Office.
Ebury is seeking a Data Scientist to join our Analytics team.
You will collaborate with business stakeholders to gather requirements and deliver data-driven insights that drive growth across multiple verticals.
Ebury's strategic growth plan relies heavily on the contributions of our Data Science team, and we are looking for enthusiastic, proactive, and curious Data Scientists who are eager to thrive in a dynamic and challenging environment.
Responsibilities:

Drive innovation in credit risk modelling by identifying opportunities for improvement, experimenting with new methodologies, and continuously refining models to enhance accuracy and performance.
Lead the development of predictive models for Credit Risk and Lending, using advanced machine learning techniques and Python in a GCP environment to optimise decision-making and risk assessment.
Leverage Large Language Models (LLMs) to process and analyse unstructured data, enhancing insights and improving credit risk modelling processes.
Collaborate with Data Engineers and Data Analysts to design, build, and deploy scalable data solutions, ensuring seamless integration of models into production and effective delivery to business stakeholders.
Mentor and guide junior Data Scientists, providing technical leadership, reviewing code and models, and fostering their growth and development within the team.
Experience and qualifications:

Advanced proficiency in Python and experience with machine learning libraries, specifically for building predictive models in Credit Risk and Lending.
Solid understanding of statistical methods and econometric models, with the ability to interpret model results and assess their performance.
Excellent communication and collaboration skills, with the ability to work closely with data engineers, analysts, and business stakeholders to translate complex data insights into actionable business strategies.
Problem-solving and critical-thinking mindset, with the ability to innovate and drive improvements in the credit risk modelling domain.
Leadership and mentoring abilities, demonstrated through experience guiding junior data scientists, providing feedback on models and code, and leading data-driven projects.
Would be nice to have:

Experience with GCP (Google Cloud Platform) tools and services, such as BigQuery, AI Platform, and Cloud Functions, for deploying scalable data solutions.
Strong knowledge of Credit Risk modelling techniques, including probability of default (PD), loss given default (LGD), and exposure at default (EAD), and other risk-related methodologies.
Expertise in leveraging Large Language Models (LLMs) for processing unstructured data, such as text analysis and sentiment analysis, to enhance risk assessment and decision-making.
Proficiency in SQL for querying and managing large datasets, as well as experience working with structured and unstructured data sources.
Please submit your application on the careers website directly, uploading your CV / resume in English.
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Read the full job description and apply online on the recuiter's web-site

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