Data Scientist FR x2
Role details
Job location
Tech stack
Job description
As a Senior Python Data Scientist, you will play a key role in designing and delivering AI-enabled data products and machine learning solutions across finance platforms. You will work closely with data engineers, AI engineers, product owners, and business stakeholders to build scalable, production-grade solutions that enhance decision-making, risk management, and operational efficiency.
Collaborating with global teams, you will contribute to the full lifecycle of data science delivery-from data ingestion and model development through to deployment, monitoring, and optimisation within a highly regulated financial environment.
The Role:
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Design and develop scalable Python-based data pipelines for financial data ingestion, transformation, and analysis
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Build and deploy machine learning models to generate predictive insights and improve platform intelligence
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Contribute to and lead end-to-end model lifecycle (MLOps) including experimentation, validation, deployment, and monitoring
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Develop AI-driven solutions, including exposure to NLP and Generative AI use cases (e.g. LLMs, RAG pipelines)
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Implement data quality, validation, and governance frameworks aligned to regulatory and security standards
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Design and build analytics dashboards and monitoring tools to track model performance and data health
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Collaborate with cross-functional teams including data engineering, product, and business stakeholders to deliver scalable AI solutions
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Translate complex analytical outputs into clear, actionable insights for senior stakeholders
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Contribute to continuous improvement and innovation across AI and data capabilities within finance platforms
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Support the development of robust, scalable, and maintainable data science solutions within enterprise environments
Requirements
We are currently looking for a dynamic individual to join our AI & Data Practice as a Senior Python Data Scientist, working within a multi-disciplinary team delivering cutting-edge AI solutions for a global banking client., To succeed in this role, you will need:
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Strong experience in Python programming, with hands-on use of libraries such as Pandas, Scikit-learn, PySpark or similar
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Proven experience building and maintaining data pipelines and data products at scale (cloud or distributed environments)
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Solid understanding of machine learning techniques, including predictive modelling, classification, regression, and/or NLP
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Experience deploying models into production with MLOps frameworks (CI/CD, model monitoring, lifecycle management)
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Strong understanding of data quality, governance, and security standards, ideally within regulated environments
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Experience working in cross-functional teams delivering end-to-end data science solutions
Strong data analysis skills with the ability to work with large, complex datasets
Desirable experience:
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Experience within banking or financial services (e.g. lending, payments, risk, customer analytics)
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Exposure to Generative AI / LLM frameworks and AI-driven automation use cases
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Experience with cloud platforms such as Azure, Databricks, or AWS
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Knowledge of AI-assisted data validation, monitoring, or model governance frameworks
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Experience building analytics dashboards (e.g. Dash, Plotly, Power BI)
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Strong stakeholder management skills, including exposure to senior or C-suite stakeholders
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Experience mentoring or guiding junior data scientists