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Data Science & AI

Senior Data Scientist

Lead advanced analytics and machine-learning workstreams from problem framing through evaluation, production integration and model governance.

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LocationLondon, UK
Working styleHybrid / client-aligned
Employment typeFull-time
Experience6–10 years

Job description

The Senior Data Scientist will lead technically demanding modelling initiatives and establish rigorous evaluation, governance and handover practices.

The role requires the ability to connect statistical methods and machine learning to business decisions, production constraints and accountable operating processes.

Key responsibilities

  • Lead model design, feature strategy, experimentation and evaluation for complex use cases.
  • Set standards for reproducibility, explainability, monitoring and model-risk documentation.
  • Review analytical methods and mentor data scientists and analysts.
  • Partner with engineering teams on deployment architecture, serving patterns and operational controls.
  • Communicate model trade-offs, uncertainty and business implications to senior stakeholders.

Qualifications

  • 6–10 years of professional data-science, machine-learning or advanced statistical-modelling experience.
  • Advanced Python and strong statistical foundations.
  • Experience leading end-to-end model development from discovery through productionisation.
  • Strong understanding of evaluation design, model monitoring and governance.

Preferred qualifications

  • Experience with deep learning, NLP, forecasting or optimisation in production.
  • MLOps experience using MLflow, Databricks, Azure ML, SageMaker or equivalent.
  • Experience in regulated or decision-critical use cases.

Benefits & employment terms

  • Compensation, leave, pension and any role-specific benefits are confirmed during the recruitment process and stated in the written offer.
  • Any client-site, travel, security-screening or right-to-work requirements are confirmed before appointment.

Nature of working style

  • The role combines hands-on modelling with technical leadership, review and stakeholder engagement.
  • Senior data scientists are expected to make uncertainty, assumptions and model limitations explicit.

Location

London-based hybrid role with client-facing workshops and technical reviews as required.

Working at RC

Delivery standards shape the employee experience

Technology roles are organised around accountable delivery, professional engineering practices and clear client or project outcomes.

01

Client-impact work

Roles are connected to defined business or delivery outcomes rather than artificial internal assignments.

02

Professional craft

Engineering, consulting and delivery decisions are expected to be explainable, maintainable and grounded in the operating context.

03

Clear ownership

Responsibilities, interfaces, quality expectations and escalation paths should be visible across teams and engagements.

04

Continuous learning

Capability grows through real delivery, peer review, feedback and exposure to changing technologies and business environments.

Hiring journey

A structured process from application to decision

The exact interview sequence may vary by role, but candidates should understand the purpose of each stage and the position they are being assessed for.

01

Apply

Submit your details against a specific published role together with the requested resume and cover letter.

02

Role review

Relevant experience, capability and work context are reviewed against the actual vacancy requirements.

03

Interview / assessment

Where appropriate, discussions explore practical experience, judgement, communication and role-specific capability.

04

Decision

Next steps are communicated in the context of the published vacancy and applicable checks or approvals.

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