Senior Data Scientist

Senior Data Scientist

Department: Data:
Analytics

Employment Type: Permanent - Full Time

Location: London, UK

Transform is looking for a Senior Data Scientist to join our Data Science team, with a strong focus on applied AI, machine learning and large language model solutions.

We are looking for someone who is technically strong, curious and pragmatic. You should be comfortable working with emerging AI technologies, but focused on delivering useful, reliable and explainable solutions rather than experimentation for its own sake.

You will be expected to bring senior‑level judgement to data science and AI work: choosing & implementing the right approach, communicating trade‑offs, managing uncertainty and helping others understand how data and AI can be used responsibly to solve real business problems.

• Design, build and deploy machine learning models to solve real‑world business problems, including classification and optimisation use cases.
• Develop and implement LLM‑based applications, including prompt engineering, fine‑tuning where appropriate, and orchestration of model/agent workflows via tools like Lang Chain.
• Build and maintain RAG, GRAPH pipelines, including document ingestion, embedding generation, vector search and retrieval strategies.
• Evaluate model performance and trade‑offs, balancing accuracy, explainability, cost and scalability.

• Use Python as the primary language for data science and ML development.
• Write, optimise and maintain SQL queries against relational databases to support analytics, feature generation, and model development.
• Collaborate on data pipelines and feature engineering to support model development and deployment.
• Apply statistical and analytical techniques to inform insights and actions from the data.
• Work with structured and unstructured data, including text‑heavy datasets used in LLM and RAG/GRAPH solutions.
• Contribute to model deployment approaches with our Dev Ops team, including APIs, batch processes and integration with existing analytics platforms.

• Work with cloud‑based platforms and services (e.g. AWS, Azure, GCP) to support model training, deployment and scaling.
• Use and evaluate modern AI tooling, frameworks and libraries (e.g. PyTorch, scikit‑learn, Lang Chain/Graph/Smith, vector databases, graph structures).
• Support experimentation and prototyping, helping move promising ideas into production‑ready solutions.

• Establish successful working relationships with business stakeholders and Domain leads to translate business problems into data science and AI solutions.
• Partner with the Lead Data Scientist to identify new AI‑driven opportunities and help shape Transform’s AI capability and offerings.
• Clearly communicate complex technical concepts, assumptions and outputs to non‑technical audiences.
• Document approaches, models and learnings to support knowledge sharing and reuse.

• Strong hands‑on experience in data science and machine learning, with evidence of delivering production or near‑production solutions.
• Solid experience building models and applying statistical techniques using Python (experience with R is desirable but not essential).
• Practical experience with LLMs, including prompt engineering and building LLM‑enabled applications.
• Experience designing or working with RAG architectures, embeddings and vector search.
• Strong understanding of machine learning fundamentals, including model evaluation, bias, overfitting and explainability.
• Experience working with cloud services for data science and AI workloads.
• Familiarity with MLOps or model deployment practices is desirable (e.g. versioning, monitoring, reproducibility).
• Strong problem‑solving skills and a pragmatic mindset. Focused on delivering value, not just experimentation.
• Ability to lead data science projects while collaborating effectively in multidisciplinary teams.
• Excellent communication skills, with the ability to explain complex concepts simply.
• Curiosity and enthusiasm for emerging AI technologies, with a desire to continuously learn and experiment.

• Rais…