At a Glance
- Tasks: Lead complex AI and data science projects while mentoring a talented team.
- Company: Dynamic tech consultancy in London with a focus on innovation.
- Benefits: Attractive salary, bonus, hybrid work model, and career development opportunities.
- Other info: Join a collaborative environment with excellent growth potential.
- Why this job: Shape the future of AI and data science while making a real impact.
- Qualifications: Extensive experience in data science consulting and strong leadership skills.
The predicted salary is between 70000 - 90000 £ per year.
Location: London (Hybrid)
Salary: £110,000 + £20,000 bonus
Overview
Our client is seeking a Director of Data Science to lead the delivery of complex AI and data science engagements whilst helping to develop and grow the Data Science capability. This is a leadership role suited to someone who combines deep technical expertise with strong consulting skills. The successful candidate will be expected to lead client engagements, shape technical solutions, contribute to business development activities and play a key role in developing the Data Science practice through mentoring, capability development and operational leadership. The role is approximately 80% client-facing delivery and 20% internal practice leadership.
Key Responsibilities
- Client Delivery
- Lead complex Data Science and AI engagements from discovery through to implementation.
- Design end-to-end technical solutions addressing business challenges.
- Act as Technical Lead across multiple client programmes.
- Provide architectural oversight and technical decision making.
- Translate business problems into scalable AI and Data Science solutions.
- Deliver high-quality consulting whilst remaining technically hands-on where required.
- Business Development
- Support Partners during client pursuits and proposal development.
- Provide technical credibility during sales engagements.
- Help shape client solutions that win new business.
- Build trusted relationships with senior client stakeholders.
- Practice Leadership
- Support the operational leadership of the Data Science practice.
- Contribute to resource planning and staffing.
- Mentor and develop consultants across the practice.
- Support performance reviews and career development.
- Drive learning and capability development initiatives.
- Help build succession within the technical leadership team.
Required Experience
Applicants should demonstrate:
- Extensive experience leading Data Science and AI consulting engagements.
- Strong consulting background with experience advising senior stakeholders.
- Experience acting as Technical Lead on enterprise-scale programmes.
- Ability to balance commercial thinking with technical delivery.
- Experience designing AI, Machine Learning or advanced analytics solutions.
- Strong solution architecture capability.
- Experience leading multidisciplinary technical teams.
- Proven ability to communicate complex technical concepts to non-technical audiences.
Essential Technical Skills
Candidates should be able to demonstrate experience in:
- Data Science solution design
- AI solution architecture
- Machine Learning
- Technical leadership
- End-to-end delivery ownership
- Client consulting
- Technical governance
- Solution implementation
- AI transformation programmes
The successful individual should remain technically credible rather than operating purely as a people manager.
Desirable Experience
Experience in one or more of the following would be advantageous:
- AI Governance
- Responsible AI
- AI Ethics
- Enterprise AI strategy
- Agentic AI transformation
- Consulting within a technology consultancy
- Building or scaling technical practices
Whilst governance and AI ethics are valued, candidates must also demonstrate the ability to lead technical delivery rather than specialising solely in policy or frameworks.
Success Measures
Performance will typically be measured against:
- Client utilisation of approximately 70-75%.
- Successful delivery of client programmes.
- Contribution to winning new work.
- Technical leadership across engagements.
- Development of the Data Science capability.
- Coaching and mentoring of consultants.
- Positive client feedback and commercial impact.
Ideal Candidate Profile
The ideal candidate combines:
- Strong consulting capability.
- Deep technical Data Science expertise.
- Commercial awareness.
- Excellent stakeholder management.
- Ability to lead both delivery and people.
- Hands-on technical credibility.
- Experience operating comfortably between business strategy and technical execution.
- Equally comfortable discussing AI strategy in the boardroom and reviewing technical solution design with engineering teams.
Director of Data Science in London employer: Method-Resourcing
As a leading employer in the heart of London, our client offers an exceptional opportunity for the Director of Data Science to thrive in a dynamic and innovative environment. With a strong focus on employee growth, the company fosters a collaborative work culture that encourages mentorship and professional development, ensuring that every team member can reach their full potential. The hybrid working model not only promotes work-life balance but also allows for meaningful engagement with clients and colleagues alike, making it an ideal place for those seeking a rewarding career in data science and AI.
StudySmarter Expert Advice🤫
We think this is how you could land Director of Data Science in London
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Method-Resourcing.
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We think you need these skills to ace Director of Data Science in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Method-Resourcing, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Method-Resourcing. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Method-Resourcing
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Method-Resourcing!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
