Help transform complex data into insights, models, and practical applications that strengthen our business. You will work closely with various stakeholders and actively contribute to innovation, automation, and better data-driven decision-making.

Tasks

• Analyse business needs and translate them into concrete data science solutions and use cases.

• Design, develop, and maintain models and algorithms, including descriptive, predictive, and prescriptive models.

• Identify non-trivial patterns in data using machine learning and statistical techniques.

• Build and operationalise decision algorithms and automated solutions in close collaboration with the business.

• Manage the full model lifecycle, from initial requirements and development through to monitoring and optimisation.

• Work with tools such as Python, R, and data science platforms to build robust and scalable solutions.

• Ensure the quality of data and models through monitoring, validation, and data cleaning.

• Support the business in understanding insights and algorithms and translate these into actionable outcomes.

• Contribute to a data-driven culture and support colleagues in adopting and using data science solutions.

• Collaborate with stakeholders across business, IT, and data teams to deliver high-impact solutions.

Ideal Profile

• Experience with data science techniques, algorithms, and machine learning.

• Hands-on experience with tools such as Python, R, or similar technologies.

• Knowledge of the LangChain stack, enabling you to independently contribute to the orchestration of AI workflows, is considered an asset.

• Strong ability to translate business questions and requirements into analytical solutions.

• An analytical and critical mindset, with the ability to quickly identify relationships and patterns in complex data.

• Strong communication skills and the ability to clearly explain complex insights to different stakeholders.

• Strong interest in AI, Intelligent Document Processing (IDP), automation, and data-driven process optimisation.

• Results-oriented and proactive, with a strong sense of ownership over your solutions.

• Preferably experience within a financial environment or other complex data environments.

• Strong attention to data quality, governance, and risk management.

• Additional knowledge or experience with Intelligent Document Processing (IDP) is considered an asset.