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Data Scientist – NLP, LLMs, & Prompt Engineering (London Area)

Careerwise
London
1 month ago
Applications closed

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Role: Data Scientist – GenAI, Python, NLP, LLMs, & Prompt Engineering

Location:Remote

Contract – 3-6 Months

Rate - £450/Day Outside IR35


Job Overview:

We are seeking a highly skilled and creativeData Scientistwith deep expertise inPython programming,Natural Language Processing (NLP), andLarge Language Models (LLMs). This role demands hands-on experience inprompt engineering, designing intelligent conversational flows, managing context windows, and interfacing with APIs such asOpenAI’s Chat Completions API. The ideal candidate should be capable of designing, evaluating, and optimizing AI systems that generate high-quality, context-aware responses.


Key Responsibilities:

  • Develop and deploy NLP solutionsusing libraries such asNLTK,SpaCy, andTextBlob.
  • Engineer prompts for LLMs usingzero-shot,few-shot,chain-of-thought, andmeta-promptingtechniques.
  • Design and refinetargeted promptsto drive intelligent behavior in AI chatbots.
  • Write Python functionsto interface with APIs, especiallyOpenAI’s Chat Completions APIand similar LLM platforms.
  • Managetoken economyandconversational contextfor long, multi-turn dialogues.
  • Architectsequential, step-by-step task flowsfor complex LLM workflows.
  • Evaluate and analyze AI-generated responses to iteratively improve prompt quality and outcome accuracy.
  • Collaborate with product, design, and engineering teams to deploy and monitor LLM-based features.
  • Conduct experiments and fine-tune prompts to enhance response relevance, coherence, and factual correctness.


Required Qualifications:

  • Proven experience withPythonand NLP libraries such asNLTK,SpaCy,TextBlob, or similar.
  • Hands-on experience working withLLMs (e.g., OpenAI, Claude, Mistral, etc.).
  • Deep understanding ofprompt engineering strategiesand conversational AI workflows.
  • Experience building and consuming RESTful APIs.
  • Strong grasp oftokenization,embedding-based memory, andcontext managementin LLMs.
  • Ability to evaluate AI outputs for quality, relevance, and consistency.
  • Familiarity with version control systems (e.g., Git) and agile development practices.


Preferred Qualifications:

  • Experience withLangChain,LlamaIndex, or other LLM orchestration tools.
  • Background inlinguistics,cognitive science, orhuman-computer interaction.
  • Prior work inchatbot development,virtual assistants, orAI-driven user interfaces.
  • Knowledge ofRAG pipelines,vector databases, andsemantic search.
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