Senior Consultant - Data Analyst

Intuita
Liverpool
3 days ago
Create job alert
Location

Intuita, Liverpool, England, United Kingdom


Base pay range

All our office locations considered: Newbury, London (satellite) & Liverpool; OR Croatia (Ĺ ibenik)


👥 The Team

We're Intuita – a fast growing consultancy making waves in both consultancy and technology. As part of the wider FSP Consulting group, we keep ambitious growth plans for this year and beyond, seeking talented individuals to complement our expert team across the business, becoming pivotal to our journey, to not just meet, but continuously exceed our client expectations!


📝 The Role

We are looking for a bright, driven, and hands‑on analyst to join our growing data consultancy.


You will bring experience of various analytical techniques in a real‑world environment, along with strong client‑relationship skills and a natural inclination to take ownership of analytical problems. You will work both independently and collaboratively to provide high‑quality solutions.


As a key player within an already experienced and talented analytics team, you are expected to provide clarity of thinking, analytical excellence, and exceptional quality across multiple deliveries. This role offers an exciting development path with exposure to all levels of our organisation and opportunities to experience all elements of the project lifecycle, from inception to delivery.


Key outputs for the role

  • Developing Approach and Plans: Detailed, thought‑through analytical approaches to solving business problems with a keen focus on client value.
  • Detailed Analytical Outputs: Fit‑for‑purpose solutions such as ML models, probabilistic models, and/or curated datasets that can be translated into actionable insights.
  • Building Business Context: Drawing contextual conclusions and actions from analytics that are highly relevant and valuable to the end client.
  • Commercial Understanding: Relating to differing client business models, identifying business challenges from analytical investigation, and demonstrating how analytical solutions can drive commercial value.
  • Presentation of value add: Presenting, illustrating, and articulating the results of analytical work and the value created for end clients.
  • Delivery Focused: Ensuring delivery is high value, on time, and client focused; comfortable working as part of a team or independently.

Your Experience

  • Proven track‑record delivering high‑quality analytics in a hands‑on capacity.
  • Understanding of machine learning models.
  • Experience with customer value, commercial, and/or marketing data.
  • Experience working with a wide range of analytics tools and techniques.
  • Experience presenting complex information to a variety of stakeholders.
  • Sound knowledge of data protection and GDPR.
  • Degree in a relevant field (e.g., Computer Science, Statistics, Mathematics, Economics or equivalent).
  • Experience working within a large corporate setting with big data volumes is highly advantageous (e.g., financial services, telco, healthcare).

Your Technical Skills

  • Python and R (highly desirable).
  • Other analytical tools, Spark or similar (highly desirable).
  • Knowledge of data warehousing, databases, and optimisation tools (highly desirable).
  • Experience with other programming languages and technologies is advantageous.

Your Characteristics

  • Proactive, dynamic, and driven by solving analytical problems, with a great eye for detail.
  • Accountable and ownership of tasks, working with tenacity and confidence to find a way.
  • Excellent communicator who can make sense of and communicate complex ideas.
  • Ability to quickly understand client context and demonstrate expertise in their business.
  • Relationship builder who can motivate and engage effectively to build trust with clients and colleagues.
  • Interest in industry trends, emerging technologies, and clients’ businesses.
  • We hire people, not job specs – if you don’t fit the exact criteria, get in touch anyway!

❔What’s in it for you?

  • 🏠 (Really) flexible and remote working: We trust you to work in the way that suits you best.
  • đź§  Genuine care and support for your health and wellbeing: Free therapy sessions, financial education, birthday treats and more.
  • ��� Incredible training and learning opportunities: You’ll be surrounded by the best and encouraged to keep growing.
  • ✨ Freedom and empowerment to own problems and explore new ideas: We allow consultants to be true consultants.
  • 🧑🤝🧑 A supportive, friendly team: We work hard and enjoy time together, whether in‑person at socials or via Slack.

đź“§ If you require any support with your application, please contact:


We look forward to hearing from YOU!


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Consultant - Data Analyst

Senior Consultant Data Analyst

Senior Consultant - Data Analyst

Senior Consultant - AI & Data, Financial Services, Data Platforms, Data Engineer, BCM, Edinburgh

Senior Consultant - Data Scientist

Consultant - Senior Consultant, Palantir Foundry Data Engineer, AI & Data, Defence & Security

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.