Data Scientist

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