Lead Data Science Consultant

Omnis Partners
London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Science Consultant - Credit Decisioning

Senior Data Science Consultant – Econometrics specialist

Western Europe Practice Head - Data Science (Machine Learning/Artificial Intelligence (ML/AI)

Data Scientist Team Lead

Machine Learning Consultant

Energy Data Scientist

Lead Data Science Consultant

Global Management Consultancy



£90k - £120k & Bonus

Hybrid – 3 days in London office & travel



We are partnered with a disruptive, highly agile, management consultancy firm, specializing in transformational advisory services to hire a number of Data Science and AI experts. With a global presence and a reputation for excellence, they partner with clients to solve complex business challenges and achieve sustainable growth, at pace.



Ambition and passion for your craft are valued very highly here. Career development is clear, rapid and achievable, and international travel is available.



As a Lead Data Science Consultant, you will employ a wide range of data science techniques to support client's strategic business aims, across a range of industries including Retail, Travel, Financial Services, Telecommunications and Technology. Typical projects include data science for performance improvement, customer engagement and pricing effectiveness, network optimisation, and machine learning to drive improved operations, including supply chain and procurement.



I’m seeking Lead Data Science experts who not only bring experience from classic management consultancy, but also brand side, in order to provide an empathetic approach to solving business problems, using advanced data and AI solutions. You will form an integral part of this growing team collaborating closely with other cross-functional teams to deliver innovative machine learning and AI solutions.



You will flex strong problem-solving skills leveraging data science skills, directly with clients’ 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.



Skills & experience required:


  • Educated to at least degree level in a quantitative subject; Machine Learning, Computer Science, Physics, Chemistry, Mathematics, Statistics, Engineering, Economics etc.
  • Proven experience in leading data science projects across a range of areas required, such as personalisation, pricing, forecasting, GenAI, NLP, classification and regression.
  • Strong programming and modelling skills using SQL and Python required, working with large volumes of complex data.
  • Expert in building and leveraging stakeholder relationships, in order to understand requirements and in turn build meaningful and impactful data science and AI solutions.
  • Management consultancy experience is strongly preferred, although similar industry side, consultative experience will be considered.


NOTE: Sponsorship is not available for this role.

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.