Transform

Data Scientist

Transform

full-time

Posted on:

Location Type: Hybrid

Location: London • United Kingdom

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Tech Stack

AWSAzureCloudGoogle Cloud PlatformPythonPyTorchScikit-LearnSQL

About the role

  • 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 LangChain.
  • 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 DevOps 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, LangChain/Graph/Smith, Vector databases, Graph Structures)
  • Support experimentation and prototyping, helping move promising ideas into production-ready solutions
  • Work closely 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

Requirements

  • 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 work independently 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
Benefits
  • Holiday entitlement, 28 days with the option to buy/sell up to 5 days
  • Day off (on or in the week of) your birthday
  • Pension eligibility, up to 5% matched contributions
  • Private healthcare
  • Life assurance
  • Enhanced maternity and enhanced paternity and shared parental leave
  • Cycle to work & electric car schemes
  • Gym & retail discounts
  • Regular social events/activities
  • A range of other benefits from our flexible benefits package
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
machine learningdata sciencePythonSQLLLM applicationsprompt engineeringRAG architecturesembeddingsvector searchstatistical techniques
Soft Skills
problem-solvingcommunicationcollaborationcuriositypragmatic mindsetindependenceenthusiasm for AI technologiesability to explain complex conceptsknowledge sharingtranslating business problems