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Data Scientist

Method Resourcing
City of London
1 week ago
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Senior Data Scientist – £75,000 to £85,000 + 3 days a week onsite


Method Resourcing is supporting a high-growth data function in central London who are building out their Data Science capability and looking for an experienced Senior Data Scientist ready to progress into a leadership role.


You’ll join a flat-structured team of five (scaling to seven), with full end-to-end ownership of modelling, deployment, and stakeholder delivery. This is a team that truly owns their products: hypothesis, modelling, deployment, monitoring. If you want breadth, autonomy, and strategic impact, this is one of the strongest environments in London.

They’re looking for someone who can already operate at a senior level: confident presenting to senior leadership, able to mentor others, and capable of stepping into a Lead role within 1–2 years.


The Role

You’ll act as the blend of:

  • Data & AI evangelist – educating stakeholders on possibilities and translating technical outcomes to business value.
  • Data specialist – shaping data science strategy, building production-ready ML models, and embedding best practice.
  • Fixer/problem-solver - helping teams refine requirements, diagnose issues, and drive real commercial outcomes.


Day-to-day you will:

  • Translate complex business problems into research questions with quantifiable objectives.
  • Identify, acquire, and work with structured and unstructured datasets.
  • Build, validate, deploy, and monitor production ML models.
  • Partner with data engineers, ML engineers, architects, and business teams to shape ML initiatives.
  • Present insights clearly through strong data visualisation and storytelling.
  • Uphold software engineering and MLOps best practices (testing, versioning, quality, automation).
  • Contribute to governance, responsible model usage, and data quality standards.
  • Mentor juniors and support code reviews.



Required Experience

You’ll need:

  • Strong Python experience and deep familiarity with mainstream ML libraries.
  • Proven experience deploying and owning ML models in production.
  • Experience working in cross-functional data teams.
  • Strong stakeholder communication skills and the ability to explain commercial impact.
  • Understanding of ML Ops vs DevOps and broader software engineering standards.
  • Cloud experience (any platform).
  • Previous mentoring experience.


Nice to have:

  • Snowflake or Databricks
  • Spark, PySpark, Hadoop or similar big data tooling
  • BI exposure (PowerBI, Tableau, etc.)


Interview Process

The process is fully structured, transparent, and efficient:

  1. Video call – high-level overview and initial discussion
  2. In-person technical presentation – based on a provided example
  3. In-person deep dive – code, design decisions, improvements
  4. Final HR video stage


Why Apply?

  • A clear, supported pathway to Lead within 1–2 years
  • High ownership, flat structure, real autonomy
  • Work with highly capable engineers, scientists, and architects
  • Build models end-to-end and see real business outcomes
  • Collaborative, modern, technically strong environment

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