Data Scientist

Data Scientist

📍 Location: London, United Kingdom

🏢 Industry: Information Services

💼 Work Setting: Hybrid

Are you passionate about leveraging Artificial Intelligence, Machine Learning, and advanced analytics to build innovative solutions that transform how users discover, access, and interact with information?

We are seeking a talented Data Scientist

to design, develop, and optimize advanced AI-powered solutions that enhance search, knowledge discovery, intelligent retrieval, and decision-support capabilities. This role offers the opportunity to work with modern AI technologies, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Natural Language Processing (NLP), and advanced machine learning techniques to deliver scalable, production-ready applications.

Key Responsibilities

Applied AI \& Machine Learning

• Develop and enhance AI-powered applications that support intelligent information retrieval, knowledge discovery, question answering, summarization, and insight generation.
• Build and improve multi-step AI workflows and intelligent automation solutions using modern orchestration frameworks.
• Apply advanced techniques in machine learning, natural language processing, generative AI, semantic search, and information retrieval.
• Contribute to prompt engineering, context optimization, grounding strategies, and AI output quality improvements.
• Evaluate emerging AI tools, models, and technologies, providing recommendations for adoption and innovation.
• Integrate structured and unstructured data sources into intelligent AI workflows to improve system performance and relevance.

Search, Retrieval \& Intelligent Knowledge Systems

• Design and optimize search and retrieval systems using lexical, semantic, vector, and hybrid search approaches.
• Develop and enhance Retrieval-Augmented Generation (RAG) architectures to improve response quality and accuracy.
• Experiment with embeddings, ranking models, retrieval strategies, and relevance optimization techniques.
• Build knowledge discovery solutions that enable users to efficiently access and explore information.
• Collaborate with engineering teams to deploy, scale, and monitor AI-driven solutions in production environments.

AI Evaluation \& Experimentation

• Design evaluation frameworks to measure the effectiveness, reliability, accuracy, and relevance of AI and search systems.
• Develop benchmark datasets, testing methodologies, and performance measurement processes.
• Conduct experiments, model evaluations, and controlled testing initiatives to validate solution effectiveness.
• Analyze results and provide actionable recommendations to improve AI model performance and user outcomes.
• Support responsible AI initiatives focused on trust, transparency, quality, and risk mitigation.

Cross-Functional Collaboration

• Partner with product managers, engineers, designers, researchers, and business stakeholders to deliver impactful AI solutions.
• Translate complex technical findings into clear and actionable insights for technical and non-technical audiences.
• Contribute to best practices, knowledge sharing, and continuous improvement initiatives within the data science organization.
• Support projects through the full lifecycle, from research and prototyping to deployment and optimization.

Required Qualifications

Education

• Master's degree or Ph.D. in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, Information Retrieval, Natural Language Processing, or a related quantitative field.

Experience

• Approximately 2 to 4 years of professional experience in Data Science, Machine Learning, Artificial Intelligence, Natural Language Processing, Information Retrieval, or related disciplines.
• Experience developing and deploying AI-powered applications in real-world or production environments.
• Proven ability to independently execute technical projects and collaborate across cross-functional teams.
• Experience conducting experimentation, model evaluation, and performance analysis.

Technical Skills

Strong experience with:

• Large Language Models (LLMs)
• Generative AI Applications
• Retrieval-Augmented Generation (RAG)
• Natural Language Processing (NLP)
• Semantic Search and Information Retrieval
• Search Ranking and Relevance Optimization
• Vector Databases and Embedding Models
• Prompt Engineering and Context Management
• Machine Learning and Statistical Analysis
• Python Programming

Experience with modern AI and machine learning frameworks such as:

• PyTorch
• TensorFlow
• Hugging Face
• LangChain
• LangGraph
• Haystack
• Distributed Machine Learning Platforms (e.g., Databricks or similar)

Analytics \& Visualization

• Experience using data visualization and analytics tools such as Tableau, Power BI, Matplotlib, Seaborn, or equivalent platforms.
• Ability to communicate insights through dashboards, reports, and visual storytelling techniques.

Preferred Qualifications

• Experience building AI assistants, conversational AI solutions, or agent-based workflows.
• Knowledge of search, recommendation, ranking, or retrieval systems.
• Familiarity with knowledge graphs, ontologies, semantic enrichment, or metadata-driven applications.
• Exposure to production machine learning systems, MLOps practices, and model deployment frameworks.
• Research or practical experience in NLP, information retrieval, search technologies, or generative AI.
• Experience working with large-scale content-rich, knowledge-intensive, or regulated data environments.