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For Companies At a Glance
- Tasks: Design and deploy AI tools, leading projects from concept to production.
- Company: Join a forward-thinking team focused on Generative AI innovation.
- Benefits: Competitive pay, flexible work options, and opportunities for skill development.
- Why this job: Make a real impact in the AI space while working with cutting-edge technology.
- Qualifications: 7+ years in Data Science/ML with strong Python and SQL skills.
- Other info: Dynamic role with potential for growth in a collaborative environment.
The predicted salary is between 48000 - 72000 £ per year.
Role Overview – 3 month contract
We are seeking an experienced Data Scientist with a strong background in Generative AI to design, build, and deploy AI-powered tools end-to-end. You will work within a small, multi-disciplinary team and take full ownership of projects—from initial discovery through to production deployment. This includes scoping use cases, building prototypes, productionising solutions, and implementing robust evaluation and governance frameworks.
Key Responsibilities
- Develop and deploy Generative AI tools independently, including chat assistants, document Q&A (RAG), summarisation, classification, extraction, and agent-based workflow automation.
- Lead evaluation and safety efforts, including the creation of offline/online test sets, and measurement of faithfulness, hallucination, bias, latency, and cost. Implement guardrails and red-teaming strategies.
- Package solutions as services, APIs, or lightweight applications (e.g., Streamlit, Gradio, React), and integrate them via CI/CD pipelines.
- Design and manage data pipelines, including chunking and embedding strategies, vector store selection, prompt versioning, and monitoring for drift and quality.
- Define model strategy, selecting and combining hosted and open-source providers, fine-tuning where appropriate, and optimising for performance, cost, and privacy.
- Translate stakeholder requirements into measurable KPIs, lead discovery sessions, document solutions clearly, and ensure maintainability.
- Apply best practices in data ethics, security, and privacy, and align solutions with service standards and accessibility requirements.
Technical Environment
- Languages & Frameworks: Python (pandas, PyTorch, Transformers), SQL
- LLM Tools: LangChain, LlamaIndex (or similar)
- Vector Databases: FAISS, pgvector, Pinecone (or similar)
- Cloud & DevOps: Azure, AWS, GCP; Docker, REST APIs, GitHub Actions
- Data & MLOps: BigQuery, Snowflake, MLflow, DVC, dbt, Airflow (preferred)
- Front-End Tools: Streamlit, Gradio, basic React (for internal tools)
Required Experience
- Minimum 7 years in Data Science/ML, including hands-on delivery of Generative AI products (beyond proof-of-concept).
- Proven ability to independently deliver production-ready tools from concept to deployment.
- Strong proficiency in Python and SQL, with solid software engineering practices (testing, versioning, CI/CD).
- Practical experience with LLMs, including prompt design, retrieval-augmented generation (RAG), tool/function calling, evaluation, guardrails, and observability.
- Strong foundation in statistics and experimentation (e.g., A/B testing), with the ability to communicate impact to non-technical stakeholders.
- Experience handling sensitive data securely and in compliance with data governance and privacy standards.
Desirable Experience
- Experience working in regulated or public-sector environments.
- Familiarity with Azure OpenAI, Vertex AI, or Amazon Bedrock.
- Lightweight fine-tuning (e.g., LoRA).
- Front-end development skills for internal tooling.
Data scientist - Gen AI employer: Opus Recruitment Solutions
Contact Detail:
Opus Recruitment Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data scientist - Gen AI
✨Tip Number 1
Network like a pro! Reach out to your connections in the data science field, especially those who have experience with Generative AI. A friendly chat can lead to insider info about job openings or even referrals that could give you an edge.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to Generative AI. Whether it's a GitHub repo or a personal website, having tangible examples of your work can really impress potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on common data science and Generative AI questions. Practice explaining your past projects and how you tackled challenges. Confidence and clarity can make all the difference!
✨Tip Number 4
Don't forget to apply through our website! We regularly update our job listings, and applying directly can sometimes put you ahead of the competition. Plus, it shows you're genuinely interested in joining our team!
We think you need these skills to ace Data scientist - Gen AI
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role, highlighting your experience with Generative AI and relevant projects. We want to see how your skills match what we're looking for, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about Generative AI and how you can contribute to our team. Keep it concise but impactful—let us know what makes you the perfect fit for this role.
Showcase Your Projects: If you've worked on any cool projects related to AI tools or data pipelines, make sure to mention them! We love seeing real-world applications of your skills, so include links or descriptions that demonstrate your hands-on experience.
Apply Through Our Website: We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Plus, it’s super easy!
How to prepare for a job interview at Opus Recruitment Solutions
✨Know Your Generative AI Inside Out
Make sure you brush up on your knowledge of Generative AI tools and techniques. Be ready to discuss your hands-on experience with LLMs, prompt design, and evaluation methods. Prepare examples of projects where you've successfully delivered production-ready tools.
✨Showcase Your Problem-Solving Skills
During the interview, highlight your ability to translate complex stakeholder requirements into measurable KPIs. Think of specific instances where you've scoped use cases or led discovery sessions, and be prepared to explain how you documented and maintained those solutions.
✨Demonstrate Your Technical Proficiency
Familiarise yourself with the technical environment mentioned in the job description. Be ready to discuss your experience with Python, SQL, and relevant frameworks like PyTorch and Transformers. If you’ve worked with CI/CD pipelines or cloud services, share those experiences too!
✨Emphasise Data Ethics and Governance
Since data ethics and privacy are crucial, prepare to talk about your experience handling sensitive data and implementing governance frameworks. Share how you've applied best practices in data security and how you ensure compliance with standards in your previous roles.