Data Scientist - Engineer

Geomiq
London
We are Manufacturing the Future! Geomiq is revolutionizing traditional manufacturing by providing engineers worldwide with instant access to reliable production methods through our digital platform. As the UK's leading Digital Manufacturing Marketplace, we offer an AI-powered B2B MaaS (Manufacturing as a Service) solution, seamlessly connecting buyers and suppliers to drive efficiency and innovation.

With our headquarters in London and quality branches in India, China, and Portugal, we collaborate with leading brands like BMW, Rolls-Royce, Brompton Bikes, and Google-even contributing to space exploration.
Check out our website!

Our platform: Geomiq offers a revolutionary platform that completely digitizes the quoting and ordering process for custom manufactured parts, ensuring the highest operational and quality outcomes. Our primary customers include Design Engineers, Mechanical Engineers, and Procurement teams, all of whom are involved in creating the world's most innovative products.
See our platform in action!

About the role:

This is a hybrid role that combines Data Engineering and Data Science , with a strong focus on applying AI in practical ways . You'll be responsible for everything from ingesting and transforming data to building dashboards, running experiments, and deploying lightweight AI-powered solutions into production.
You'll work directly with the product and operations teams to solve real business problems fast - with full autonomy and a mandate to make things happen. Important: This is not an academic AI/ML role. You won't be building LLMs from scratch. Instead, you'll use off-the-shelf models, prompt engineering, and smart automation to drive outcomes.

Main responsibilities:

🔧 Data Engineering
  • Maintain and evolve pipelines (BigQuery + dbt)
  • Design and manage ETL/ELT workflows, including API ingestion (e.g. Monday, HubSpot)
  • Build data marts, internal views, and support dashboarding
  • Ensure clean, well-documented, and reliable data flows
📊 Data Science & Analytics
  • Own deep-dive analysis (e.g. On-Time Delivery %, NCR trends, quote conversion)
  • Collaborate with ops/product to identify high-leverage data opportunities
  • Design and analyze A/B tests
  • Create dashboards and datasets for sales, quality, and production teams
Applied AI (Using Existing Models)
  • Apply LLMs (e.g. GPT, Claude, Gemini) to workflows and internal tools
  • Fine-tune or prompt models for tasks like:
  • NCR root cause suggestions
  • Supplier performance classification
  • Delivery risk flagging
  • Deploy lightweight APIs using FastAPI or Flask (GCP Cloud Run + Docker)
Experience Required:
  • Direct, hands-on experience with GCP (BigQuery, Vertex AI, Cloud Run)
  • Strong SQL complex querying
  • Python for analytics, backend logic, and model prototyping
  • Familiarity with LLM APIs , prompt engineering , embeddings , and traditional ML (e.g. XGBoost , scikit-learn )
  • Comfortable deploying tools using Docker , Flask/FastAPI , and GCP services
  • Ability to work independently and iterate quickly toward high-quality outcomes
  • Full-stack data capability, from pipelines to dashboards to AI-powered APIs
  • Hands-on, impact-driven, and solution-oriented approach
  • Experience applying existing ML/LLM tools to automate or enhance workflows
  • Ability to thrive in lean teams and take full ownership of the data domain
Desired experience:
  • Experience with Metabase and dbt
  • Familiarity with manufacturing, logistics, or supplier operations
  • Experience building internal agents, dashboards, or automation tools
  • Light exposure to data governance or compliance
  • Interest in working at the intersection of manufacturing, data, and AI
Benefits:
  • Working directly with the leadership team
  • High growth /high impact position
  • Competitive Salary: We offer pay that reflects your skills and the value you bring.
  • Stocked Kitchen: Enjoy snacks, fresh fruit, and drinks all day.
  • 23 Days Annual Leave: Recharge with 23 days off, plus bank holidays.
  • Birthday Off: Take an extra day to celebrate your birthday.
  • Christmas Shutdown: Relax over the holidays with additional company-wide time off.
  • Pet-Friendly Office: Bring your dog to our pet-friendly workspace.
  • Team Events: Connect with colleagues through monthly team-building activities.
  • Career Growth: Benefit from our focus on internal promotions and development.
  • Cycle to Work Scheme: Save on commuting, reduce emissions, and stay active.
  • Expanding Perks: Look forward to more benefits as we grow
Department Data Engineering Locations London, UK Remote status Hybrid Employment type Full-time
Posted 2025-10-15

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