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Managing Consultant - London Area, United Kingdom - Omnis Partners
Description
VP – Data Science & AI
Global Management Consultancy
£85k - £120k
Hybrid – 3 days in London office
Our client is a leading consulting firm specializing in transformational advisory services. With a global presence and a reputation for excellence, they partner with clients to solve complex business challenges and achieve sustainable growth.
As the VP - Data Science, you will be at the forefront of developing and executing data-driven strategies that optimize business performance and enhance decision-making processes for a wide variety of end clients. You will project lead lean teams of Data Scientists, collaborating closely with cross-functional teams to deliver innovative machine learning and AI solutions.
You will need to apply hands on skills in coding and modelling as well as lead small yet agile project teams of machine learning and AI experts. You'll work with client's senior leadership teams looking to achieve results FAST, therefore you need to be skilled in, and comfortable with, delivering the most impactful solution (even if not perfect) in short sprints.
Naturally at this grade, you will have the chance to employ and flex those senior leadership qualities, working in harmony with clients to empathise, understand and dissect their challenges, as well as pull on your depth of expertise as to 'the art of what's (technically, and commercially) possible'.
Typical Data Science and AI projects relate to pricing, supply chain, operations, performance improvement and more
Culture is key - we are also looking for passionate, authentic, enthusiastic data science and AI practitioners, who can delight, impress and engage non-technical stakeholders, with their credibility, exceptional problem-solving skills and ability to deliver commercial results.
In return, you will work amongst like minded people, colleagues with whom you will form a close bond and partnership with, in order to deliver best in class data science services.
Skills & experience required:
