Staff Data Designer
New
M
MethodData and AI consulting
Remote First with occasional need to travel to the London office.Full-TimeStaff
Salary not disclosed
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Job Details
- Experience
- 4+ years in data science, ML engineering or data consulting, including leading client-facing projects.
- Required Skills
- AWSPythonSQLGCPMachine LearningGenerative AILangChain
Requirements
- Have 4+ years in data science, ML engineering, or data consulting, including leading client-facing projects.
- Have experience designing and deploying ML models that predict customer needs and behaviours, such as personalisation, recommendation, lead scoring, CLTV, churn, or risk models.
- Know recommendation and personalisation techniques, including collaborative and content-based filtering, matrix factorisation, embeddings, contextual personalisation, and UI personalisation.
- Have hands-on experience with LLMs and GenAI, including prompt design, RAG, vector databases, and frameworks such as LangChain/LangGraph or Hugging Face.
- Have strong Python and SQL skills and working knowledge of pandas, scikit-learn, PyTorch or TensorFlow, and XGBoost.
- Have experience with cloud data and ML platforms, ideally AWS (S3, SageMaker Pipelines, Glue) and/or GCP, and MLOps practices including MLflow, CI/CD, Docker, and infrastructure as code.
- Be able to build BI dashboards using Power BI or Tableau and visual prototypes using tools such as Streamlit or React.
- Have excellent written, verbal, and visual communication skills and experience presenting to senior, non-technical stakeholders.
- Be confident running workshops and discovery sessions and turning ambiguous problems into clear scope.
- Desirable experience includes pre-sales, agentic AI, NLP, forecasting, Monte Carlo simulation, reinforcement learning, data engineering, and hiring or mentoring.
- A STEM degree or equivalent practical experience is desirable.
Responsibilities
- Lead or co-lead data and AI engagements end to end, owning the quality of data deliverables and the structure of the work.
- Combine design thinking and user-centric techniques with quantitative analysis to diagnose and design data-led products and services.
- Facilitate technical discovery sessions and client workshops to uncover pain points, opportunities, and available data sources.
- Design and build predictive and prescriptive ML models, including personalisation, recommendation, lead scoring, CLTV, forecasting, and risk detection.
- Design and prototype secure, compliant GenAI and LLM solutions, including RAG, agentic workflows, and summarisation.
- Build BI dashboards and data products, and define KPIs and analytics layers to track adoption and outcomes.
- Develop data strategies, data-to-decision mappings, and phased roadmaps connecting business objectives to technical delivery.
- Present work to client stakeholders up to C-suite and board level using visual approaches for non-technical audiences.
- Write documentation and handovers so clients can take solutions into production.
- Scope projects, write proposals and SOWs, build rapid POCs, champion MLOps and code quality, review work, and mentor junior colleagues.
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