At a Glance
- Tasks: Drive AI adoption and enhance business performance through data insights and stakeholder collaboration.
- Company: PE-backed consultancy in the finance sector, focused on innovation and growth.
- Benefits: Competitive salary, 40% bonus, and exposure to transformative business practices.
- Other info: Fast-paced role with opportunities for professional growth and leadership engagement.
- Why this job: Shape the future of AI in a dynamic environment and make a real impact.
- Qualifications: Experience in consulting or project delivery with strong communication skills.
The predicted salary is between 63000 - 77000 £ per year.
PE-backed consultancy in the Finance Space
£65k – £80k + 40% bonus
Covent Garden, London | Onsite
What's in it for me?
- Exposure to working in a PE-backed business. With more investment flooding into the market, gaining direct exposure to how a PE-backed organisation transforms, grows and prioritises commercial gain is invaluable in today's highly competitive candidate market.
- Take on a pivotal role in enabling AI adoption across the organisation, wearing a commercial hat to boot.
- Take your consulting skills 'in-house' and support teams vertically and horizontally to embed, own and ensure success of AI, as well as demonstrating commercial gain.
A rising role in the current market.
We are partnering with a successful PE-backed consultancy to appoint a commercially focused Data & AI Delivery Consultant. The business has already established a strong data architecture and launched several successful AI applications. It is now looking for someone to help shape and deliver the next phase of its data, AI and automation roadmap. This is not a developer or engineering role.
You will act as the bridge between business stakeholders, Product and Engineering, identifying valuable opportunities, translating business challenges into clearly scoped initiatives and ensuring new solutions are successfully delivered and embedded.
You will:
- Engage with commercial and client-facing teams to understand their priorities, challenges and workflows.
- Identify where data, AI and automation could improve client delivery, efficiency, quality or commercial performance.
- Assess and prioritise opportunities based on value, feasibility, risk and effort.
- Build business cases, define success measures and translate ideas into clear delivery scopes.
- Coordinate delivery across stakeholders, Product and Engineering.
- Support user testing, feedback and iteration throughout the build process.
- Lead rollout, training and adoption across the business.
- Track outcomes and demonstrate the commercial impact of new solutions.
The Engineering team will undertake the majority of the technical build. Your responsibility is to ensure the right problems are being solved, and that the resulting tools genuinely work for the people using them.
You are likely to have proven experience in consulting, product, proposition, transformation, project delivery, business analysis or a commercially focused data role.
You will bring:
- Strong commercial judgement and the ability to connect technology with measurable business value.
- Excellent stakeholder management and communication skills.
- Experience owning cross-functional initiatives from discovery through to delivery and adoption.
- A structured approach to prioritisation, project management and problem-solving.
- Confidence working with senior, commercial and technical stakeholders.
- The initiative and resilience to thrive in a fast-paced, evolving PE-backed environment.
You do not need to be a developer. However, you should have enough technical curiosity and understanding to work credibly with Product and Engineering teams. Experience with data, analytics, AI, automation, Power BI, Microsoft Power Platform or tools such as n8n would be advantageous. Previous exposure to financial services, professional services or another regulated environment would also be valuable, but is not essential.
The opportunity
This is a highly visible role with the opportunity to shape an important business-wide agenda, work closely with senior leadership and turn emerging data and AI capabilities into tangible commercial outcomes.
Data & AI Consultant in London employer: Omnis Partners
As the Head of Marketing Effectiveness for a leading global consumer brand based in London, you will thrive in a dynamic and innovative work culture that prioritises creativity and collaboration. The company offers competitive compensation, robust employee growth opportunities, and a hybrid working model that promotes work-life balance, making it an excellent employer for those seeking meaningful and rewarding careers in marketing.
StudySmarter Expert Advice🤫
We think this is how you could land Data & AI Consultant in London
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We think you need these skills to ace Data & AI Consultant 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!
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Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Omnis Partners. 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 Omnis Partners
✨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!
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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
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✨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.
