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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: Collaborate with experts and build a portfolio showcasing your generative AI projects.
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 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 your previous projects that involve AI or machine learning. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will showcase your problem-solving skills.
✨Tip Number 4
Practice explaining complex technical concepts in simple terms. Since the role requires communicating with non-technical stakeholders, being able to break down intricate ideas will set you apart from other candidates.
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 coursework that align with the role's requirements.
Showcase Relevant Projects: Include links or brief descriptions of prior projects that demonstrate your hands-on experience with generative AI, prompt engineering, or deploying models. This will help illustrate your practical skills.
Prepare for Technical Questions: Be ready to discuss your understanding of vector databases, evaluation metrics, and any tools you've used in your projects. Practising explaining complex ideas in simple terms will be beneficial for interviews.
How to prepare for a job interview at Aspect
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and any machine learning frameworks you've used. Highlight specific projects where you've implemented RAG concepts or worked with vector databases, as this will demonstrate your hands-on capabilities.
✨Communicate Clearly
Since the role involves explaining complex ideas to non-technical audiences, practice articulating your thoughts on generative AI and LLMs in simple terms. This will show that you can bridge the gap between technical and business perspectives.
✨Demonstrate Your Curiosity
Express your enthusiasm for AI and how it can drive business growth. Share examples of how you've explored new technologies or tackled challenging problems in your previous work or studies, showcasing your inquisitive nature.
✨Prepare for Practical Assessments
Expect to engage in practical assessments or case studies during the interview. Brush up on your skills related to prototyping RAG pipelines and fine-tuning models, as these are key aspects of the internship role.
