Data Scientist

bp
London
1 week ago
Applications closed

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Data Scientist - Supply Chain Optimisation

Job Title: Data Scientist

Job Location: Canary Wharf (Hybrid)

Contract Length: Until 31/12/2026

Industry: Oil and Energy, Tech

Working Hours: 8 per day/40 per week


Role Overview:

  • Design, develop, and maintain production-grade AI applications and services using modern software engineering practices (CI/CD, testing, observability, cloud-native design).
  • Define and implement foundational platforms and tools (e.g., conversational bots, AI-powered search, unstructured data processing, GenBI) that are reusable and scalable across the enterprise.
  • Participate in cross functional team initiatives-embedded projects with business stakeholders -to rapidly build and deploy AI solutions that solve high-priority business problems.
  • Evaluate and integrate existing AI tools, frameworks, and APIs (e.g., LLMs, vector DBs, retrieval-augmented generation, AI agents) into robust applications.
  • Champion automation in workflows - from data management ingestion and pre-processing to evaluation, to model integration and deployment.
  • Collaborate with data scientists, product managers, and other engineers to ensure end-to-end delivery and reliability of AI products.
  • Stay current with emerging AI technologies but prioritize practical application and delivery over experimental research.
  • Contribute to the internal knowledge base, tooling libraries, and documentation to scale AI engineering best practices across the organization.


What you will have:

  • Professional software engineering experience: ability to independently design and ship complex systems in production.
  • Strong programming skills in Python (preferred), Java, or similar languages, with experience in developing microservices, APIs, and backend systems.
  • Strong problem-solving skills and the ability to balance engineering rigor with delivery speed.
  • Solid understanding of software architecture, cloud infrastructure (AWS, Azure, or GCP), and modern DevOps practices.
  • Experience integrating machine learning models into production systems (e.g., LLMs via APIs, fine-tuning, RAG patterns, embeddings, agents and crew of agents etc.).
  • Ability to move quickly while maintaining code quality, test coverage, and operational excellence. Preferred:
  • Familiarity with AI/ML tools such as LangChain, Haystack, Hugging Face, Weaviate, or similar ecosystems.
  • Hands-on experience with Retrieval Augmented Generation applications, AI agents and systems built around them.
  • Experience using GenAI frameworks such as LlamaIndex, Crew AI, AutoGen, or similar agentic/LLM orchestration toolkits.
  • Exposure to working with unstructured data (documents, conversations, images) and transforming it into usable structured formats.
  • Experience building chatbots, search systems, or generative AI interfaces.
  • Background in working within platform engineering or internal developer tools teams.
  • Prior experience working in an embedded (forward-deployed) team model with business stakeholders.
  • Experience building production grade, reliable AI applications


We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, colour, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status.

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