Senior Consultant - Data Analyst

Intuita - Vacancies
Liverpool
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Consultant, Data Science (Customer Data)

Senior Consultant, Data Science (Customer Data)

Data Analyst Senior Consultant, Assistant Manager, Manager - Belfast

Data Engineer - (Python, SQL, Machine Learning) - Robotics

SAS Data Engineer

SAS Data Engineer

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


👥 The Team

We’re Intuita – a fast growing consultancy that’s making waves in both the consultancy and technology space! Now as part of the wider FSP Consulting group, we continue with our ambitious growth plans for this year and beyond; we are looking for talented individuals to complement the team of experts we already have working across our business, becoming a pivotal part of 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, as well as the ability to maintain strong client relationship skills and the 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 to multiple deliveries.


This role provides an exciting development path with exposure to each level of our organisation and opportunities to experience all elements of the project lifecycle, from inception through 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 to business problems such as ML models, Probabilistic models, and / or curated datasets that can be easily 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: Able to relate to differing client business models, identification of business challenges from analytical investigation and/or demonstration of how analytical solutions can drive commercial value.
  • Presentation of value add: Ability to present, illustrate and articulate the results of analytical work and the value created for end clients.
  • Delivery Focused: Ability to ensure delivery is high value, on time and client focused. You must be equally comfortable working either as part of a team or displaying self‑starter skills whilst working independently.

🧑 A bit about you

We have a strong ethos of accountability, quality and integrity at Intuita and like to work with people who believe in this too. We also really value collaboration and teamwork, working together to solve problems but always having fun along the way. We want you to bring your own personality and approach to the role, but you’ll also need:


Your Experience:

  • Proven track‑record delivering high‑quality analytics in a hands‑on capacity.
  • Understanding of machine learning models.
  • Has worked 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).
  • Work within a large corporate setting with big data volumes is highly advantageous (e.g., financial services, telco, healthcare).

Your technical skills:

  • SQL (critical)
  • Excel (critical)
  • 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.
  • Takes accountability and ownership of tasks, works with tenacity and confidence to find a way.
  • An excellent communicator who can make sense of and communicate complex ideas.
  • Ability to quickly understand client context and demonstrate expertise in their business.
  • A relationship builder, with the ability to motivate and engage effectively to build trust with clients and colleagues.
  • An interest in industry trends, emerging technologies, and client’s businesses.

If you don’t fit the above criteria exactly and are interested in working for us, get in touch anyway – we hire people, not job specs!


❔What’s in it for you?

  • 💷 Salary: £circa £50,000 - £70,000 per annum DOE
  • 🏠 (Really) flexible and remote working – we don’t mind when, where or how you work; you are trusted to work in the way that suits you best.
  • 🧠 Genuine care and support for your health and wellbeing – free therapy sessions, financial education, birthday treats and much more.
  • 🚀 Incredible training and learning opportunities – you’ll be surrounded by the best in the business and encouraged to keep growing.
  • ✨ Freedom and empowerment to own problems and explore new ideas – we allow our consultants to actually be consultants, not just bodies.
  • 🧑🤝🧑 A supportive, friendly team – we work hard and enjoy spending time together, whether it’s in‑person at socials or via silly Slack conversations.

📧 If you require any support with your application, please contact:


We look forward to hearing from YOU!


#J-18808-Ljbffr

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.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.