Data Scientist
New
United KingdomFull-Time
Salary not disclosed
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Job Details
- Required Skills
- PythonCloud ComputingMachine LearningData engineeringSparkLLMGenerative AIDistributed SystemsPySpark
Requirements
- Strong professional experience with Python and/or PySpark in data engineering, data science, or AI-focused projects.
- Hands-on expertise working with Apache Spark and distributed data processing environments.
- Experience designing and implementing Generative AI solutions, including AI agents, MCPs, RAG architectures, and LLM-based applications.
- Knowledge of AI evaluation methodologies, monitoring, observability, and production deployment best practices for AI systems.
- Ability to develop scalable, high-performance solutions within enterprise-grade environments.
- Familiarity with modern Generative AI frameworks, orchestration tools, and machine learning workflows.
- Experience working with cloud environments and distributed architectures is highly desirable.
- Previous exposure to banking, fintech, or financial services projects is considered an advantage.
- Strong analytical thinking, problem-solving skills, and the ability to work effectively in collaborative agile teams.
- Excellent communication skills with the ability to contribute to technical discussions and interact with multidisciplinary stakeholders.
- Continuous learning mindset and strong interest in emerging AI technologies and innovation.
Responsibilities
- Design and develop advanced Generative AI solutions using intelligent agents, large language models, and modern AI architectures.
- Build and optimize large-scale data processing pipelines using Python, PySpark, Spark, and distributed data technologies.
- Integrate AI-driven capabilities into scalable data environments while ensuring high performance, reliability, and maintainability.
- Collaborate with cross-functional technical teams to deliver innovative AI and data science solutions within agile project environments.
- Participate in architectural discussions and contribute to the evolution of data and AI platforms aligned with business objectives.
- Develop scalable and production-ready AI components with strong focus on monitoring, observability, and evaluation of AI agents.
- Implement and maintain RAG-based solutions, Guardrails, and orchestration frameworks to enhance AI system performance and reliability.
- Support continuous improvement initiatives by identifying opportunities for optimization, automation, and innovation across data and AI workflows.
- Contribute to technical documentation, best practices, and knowledge sharing within the broader engineering and data teams.
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