- Company Name
- Opus Recruitment Solutions
- Job Title
- Data scientist - Gen AI
- Job Description
-
Job title: Data Scientist – Generative AI
Role summary: Short‑term (3‑month) contract to independently design, build, deploy, and govern end‑to‑end Generative AI solutions for a multidisciplinary team. Own the full project lifecycle from discovery, prototyping, productionization, to continuous monitoring and optimization.
Expectations: • Deliver production‑ready AI tools (chat assistants, RAG, summarization, classification, extraction, agent workflows) that meet performance, cost, and privacy goals.
• Lead safety, evaluation, and guardrail development, creating test sets and metrics for hallucination, bias, latency, and cost.
• Package solutions as APIs or lightweight UIs (Streamlit, Gradio, React) and integrate with CI/CD pipelines.
• Translate stakeholder requirements into measurable KPIs, conduct discovery sessions, and maintain clear documentation.
• Apply best practices in data ethics, security, and accessibility, ensuring compliance with governance standards.
Key responsibilities
1. Build and deploy Generative AI tools (chat assistants, RAG, summarization, classification, extraction, workflow automation).
2. Design, implement, and monitor data pipelines: chunking, embedding, vector store selection, prompt versioning, drift detection.
3. Define model strategy: select, combine, and fine‑tune hosted or open‑source LLMs; optimize for performance, cost, and privacy.
4. Create and maintain evaluation frameworks: offline/online test sets, faithfulness, bias, hallucination, latency, cost metrics.
5. Package solutions as services/APIs or lightweight apps; integrate via Docker, GitHub Actions, and cloud CI/CD (Azure, AWS, GCP).
6. Lead discovery, stakeholder communication, KPI definition, and documentation.
7. Enforce data ethics, security, privacy, and accessibility guidelines.
Required skills
- 7+ years in Data Science/ML with proven delivery of Generative AI products.
- Strong Python (pandas, PyTorch, Transformers) and SQL expertise; software engineering practices (testing, versioning, CI/CD).
- Deep experience with LLMs: prompt design, RAG, tool/function calling, evaluation, guardrails, observability.
- Familiarity with LangChain, LlamaIndex, FAISS, pgvector, Pinecone (or equivalents).
- Cloud and DevOps: Azure, AWS, GCP; Docker, REST APIs, GitHub Actions.
- Data & MLOps: BigQuery, Snowflake, MLflow, DVC, dbt, Airflow.
- Front‑end: Streamlit, Gradio, basic React for internal tooling.
- Statistical modeling, experimentation (A/B testing), and impact communication to non‑technical stakeholders.
- Secure handling of sensitive data and compliance with data governance/privacy.
Required education & certifications
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related field.
- Certifications in cloud platforms (Azure/AWS/GCP) or MLOps are advantageous.
(End)
Staines-upon-thames, United kingdom
On site
12-09-2025