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- Tasks: Join us as a Data Scientist Intern to design and prototype AI solutions.
- Company: Aspect is a leading property-maintenance team in London, operating 24/7.
- Benefits: Gain hands-on experience, mentorship, and work on real AI projects.
- Why this job: Be part of a cutting-edge tech environment with real-world impact and growth opportunities.
- Qualifications: Pursuing or completed a Master's in Data Science or related field; strong Python skills required.
- Other info: Work with advanced AI tools and collaborate with experts in a supportive culture.
About Us
Covering more trades than anyone else, Aspect is one of London’s largest property-maintenance teams. We operate 24/7, helping thousands of residential and commercial customers every month. After 15 years of steady growth, we have bold plans to scale even faster over the next three years—and we’re harnessing generative AI to get there. If you’re excited by cutting-edge tech and real-world impact, join us at this pivotal moment.
The Role
We’re looking for an inquisitive, hands-on Data Scientist Intern (Generative AI / LLM / RAG) for a 4-month internship programme. You’ll join our data and product teams to design, prototype, and evaluate solutions that leverage Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) to improve customer experience, internal workflows, and decision-making.
Think: building chatbots that tap our knowledge base, fine-tuning models on call-centre transcripts, or creating smart agents that surface the right maintenance engineer in seconds. You’ll see first-hand how generative AI moves the needle for a growing business.
You Will
- Prototype RAG pipelines—set up vector stores, devise retrieval strategies, and iterate on prompts
- Fine-tune or adapt foundation models (e.g., Llama-3, GPT-4o) to company-specific data
- Build evaluation harnesses to measure accuracy, latency, and hallucination rates
- Work with Python, LangChain/LlamaIndex, Hugging Face, and cloud LLM endpoints (OpenAI, Azure AI, etc.)
- Collaborate with analysts, engineers, and ops teams to turn PoCs into deployable micro-services
- Present findings to stakeholders, translating technical insight into business value
- Contribute to best-practice docs on prompt engineering, model versioning, and AI governance
About You
You’re a problem-solver who loves experimenting, learning fast, and shipping usable prototypes. You pair solid theory with the scrappiness needed in a scale-up environment.
Essential
- Currently pursuing (or recently completed) a Master’s in Data Science, Machine Learning, AI, or similar
- Strong Python skills and experience with a modern ML/AI stack (PyTorch, Transformers, or equivalent)
- Familiarity with vector databases (FAISS, Pinecone, Qdrant, Chroma, etc.) and RAG concepts
- Ability to explain complex ideas clearly to non-technical audiences
- Curiosity about how AI can drive tangible business growth
Nice to Have
- Hands-on work with LangChain, LlamaIndex, or similar orchestration frameworks
- Knowledge of prompt-engineering techniques and evaluation metrics (BLEU, ROUGE, BERTScore, etc.)
- Experience deploying models on Azure, AWS, or GCP
- Understanding of MLOps tools (MLflow, Weights & Biases, GitHub Actions)
- Prior projects that show a creative application of generative AI (link or brief description)
What You’ll Gain
- Ownership of real AI projects that reach production users
- Mentorship from senior data scientists and engineers
- Deep exposure to LLM tooling, RAG architectures, and AI evaluation best practices
- A portfolio of deliverables demonstrating end-to-end generative-AI workflows
- A collaborative culture that encourages experimentation and values your ideas
Data Scientist Intern employer: Aspect
Contact Detail:
Aspect Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist Intern
✨Tip Number 1
Familiarise yourself with the latest advancements in generative AI and Large Language Models (LLMs). Understanding how these technologies work will not only help you during interviews but also demonstrate your genuine interest in the role.
✨Tip Number 2
Engage with online communities or forums related to data science and AI. Networking with professionals in the field can provide insights into the company culture and expectations, which can be invaluable during your application process.
✨Tip Number 3
Prepare to discuss any relevant projects you've worked on, especially those involving Python and machine learning frameworks. Being able to articulate your hands-on experience will set you apart from other candidates.
✨Tip Number 4
Practice explaining complex technical concepts in simple terms. Since the role requires communicating with non-technical stakeholders, showcasing your ability to bridge that gap can make a strong impression.
We think you need these skills to ace Data Scientist Intern
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant skills and experiences related to data science, machine learning, and AI. Emphasise your Python proficiency and any projects involving LLMs or RAG concepts.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for generative AI and how it can impact business growth. Mention specific projects or experiences that demonstrate your problem-solving abilities and curiosity.
Showcase Relevant Projects: Include links or brief descriptions of prior projects that illustrate your hands-on experience with generative AI, prompt engineering, or deploying models. This will help you stand out as a candidate.
Prepare for Technical Questions: Be ready to discuss your understanding of AI concepts, vector databases, and evaluation metrics during the interview process. Practising how to explain complex ideas clearly will be beneficial.
How to prepare for a job interview at Aspect
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and any modern ML/AI stacks you've worked with. Highlight specific projects where you've used tools like PyTorch or Transformers, as this will demonstrate your hands-on capabilities.
✨Demonstrate Your Problem-Solving Ability
Think of examples where you've tackled complex problems, especially in a fast-paced environment. Be ready to explain your thought process and how you approached finding solutions, particularly in relation to generative AI.
✨Communicate Clearly
Since the role involves explaining technical concepts to non-technical stakeholders, practice articulating your ideas simply and clearly. Use analogies or relatable examples to make your points more accessible.
✨Prepare Questions About the Company
Research Aspect and its use of generative AI. Prepare insightful questions that show your interest in their projects and how you can contribute to their goals. This will demonstrate your enthusiasm and proactive attitude.
