At a Glance
- Tasks: Lead the development of innovative Generative AI solutions for real-world business challenges.
- Company: Join a forward-thinking tech company at the forefront of AI innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative team environment with a focus on continuous learning and development.
- Why this job: Make a significant impact by creating cutting-edge AI applications that transform industries.
- Qualifications: 5+ years in Data Science with hands-on experience in LLMs and Generative AI.
The predicted salary is between 63000 - 77000 £ per year.
We are looking for a highly capable and innovative Data Scientist with experience in Generative AI to join our Data Science Team.
You will lead the development and deployment of Gen AI solutions, including LLM-based applications, prompt engineering, fine-tuning, embeddings, and retrieval-augmented generation (RAG) for enterprise use cases.
As part of your duties, you will be responsible for
- Design and build Generative AI solutions using Large Language Models (LLMs) for business problems across domains like customer service, document automation, summarization, and knowledge retrieval.
- Fine-tune or adapt foundation models using domain-specific data.
- Implement RAG pipelines, embedding models, vector databases (e. g., FAISS, Pinecone, Chroma DB).
- Collaborate with data engineers, MLOps, and product teams to build end-to-end AI applications and APIs.
- Develop custom prompts and prompt chains using tools like Lang Chain, Llama Index, Prompt Flow, or custom frameworks.
- Evaluate model performance, mitigate bias, and optimize accuracy, latency, and cost.
- Stay up to date with the latest trends in LLMs, transformers, and Gen AI architecture.
- Qualifications and experience we consider to be essential for the role:
- 5+ years of experience in Data Science / ML, with 1+ year hands‑on in LLMs / Gen AI projects.
- Strong Python programming skills, especially in libraries such as Transformers, Lang Chain, scikit-learn, Py Torch, or Tensor Flow.
- Experience with Open AI (GPT-4), Claude, Mistral, LLa MA, or similar models.
- Knowledge of vector search, embedding models (e. g., BERT, Sentence Transformers), and semantic search techniques.
- Ability to build scalable AI workflows and deploy them via APIs or web apps (e. g., Fast API, Streamlit, Flask).
- Familiarity with cloud platforms (AWS/GCP/Azure) and MLOps best practices.
- Excellent communication skills with the ability to translate technical solutions into business impact.
Skills and Personal attributes we would like to have
- Experience with prompt tuning, few-shot learning, or Lo RA-based fine-tuning.
- Knowledge of data privacy and security considerations in Gen AI applications.
- Familiarity with enterprise architecture, SDLC, or building Gen AI use cases in regulated domains (e. g., finance, insurance, healthcare).
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Generative AI Data Scientist in London employer: TechYard
Join a dynamic consultancy that champions innovation in Data & AI transformation, where your expertise as a Senior Cloud Engineer will be valued and nurtured. With a strong emphasis on collaboration and professional growth, you'll have access to cutting-edge tools and technologies while working alongside industry leaders in a supportive environment. Located in a vibrant tech hub, this role offers unique opportunities to engage with enterprise clients and make a tangible impact on their AI initiatives.
StudySmarter Expert Advice🤫
We think this is how you could land Generative AI Data Scientist in London
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like TechYard.
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We think you need these skills to ace Generative AI Data Scientist in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at TechYard, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at TechYard. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at TechYard
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at TechYard!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
