Data Science Specialist

We're Hiring: Data Science Operations & Strategy Consultant

Hybrid Working: London 3 days/week in-office

Contract: 6 months

My client is looking for an experienced Data Science Operations & Strategy Consultant to join our team in London on a hybrid basis.

Client is a data-driven market insights and forecasts enable global organizations to navigate risks and make strategic investment decisions. As we continue embedding and scaling our Data Science capabilities across the business, we are seeking a senior consultant to advise business leadership on optimizing our operating model, team structure, delivery processes, and stakeholder management.

Key Responsibilities

• Optimize Operations: Assess and refine current delivery processes, governance, and operating models to reduce friction and boost collaboration across cross-functional teams (Product, Content, and Software).


• Strategic Roadmap: Review delivery roadmaps, optimize short-term resourcing, and help construct a medium-term team development plan for 2027 P&L planning.


• Standards & Best Practices: Refine end-to-end standards for data science development, testing, and deployment to balance technical rigor with commercial delivery.


• Team & Capability Design: Collaborate with leadership to define future team structures, role designs, and hiring strategies for permanent talent and contractors.


• Mentorship: Coach existing team members through process updates and modern cross-functional ways of working.

Skills & Qualifications

• Data Science & ML Expertise: Strong academic background (e.g., Master’s degree in Data Science or a scientific discipline with significant ML focus) alongside practical data science experience.


• Software Engineering Discipline: Proven ability to write production-grade Python code, enforce unit testing, exception handling, and logging, and manage full deployment without handing prototypes off to separate teams.


• Operations & Strategy Track Record: Experience assessing and improving operating models, delivery processes, and team effectiveness within data-driven environments.

Technical Stack:

• Core: Python, Git


• Cloud & DevOps: AWS, Docker, EKS, Kubernetes awareness, and automated CI/CD deployment pipelines


• Concepts: Configuration management (separating configuration from code), dimensionality reduction, and prompt engineering/LLMs


• Communication: Exceptional written and verbal skills, with a track record of producing clear technical documentation and aligning cross-functional stakeholders.

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