Data Scientist

Proactive Appointments
Bridgwater
2 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist (Government)

Data Scientist (NLP & LLM Specialist)

Data Scientist | Bristol (2 days onsite) | £50,000-£70,000 + Benefits

We're recruiting on behalf of our client for an exciting Data Scientist position based in Bristol. This role offers an excellent opportunity for someone who wants to play a key part in elevating how data, analytics, and technology are used across the organisation.

As a Data Scientist, you'll work closely alongside the Reporting & Analytics team, engaging directly with business stakeholders to understand their needs and translate data into meaningful insights. You'll be delivering advanced analytics, predictive modelling, and machine learning solutions that support smarter decision-making and help shape the business's future direction.

This is a role with real influence - you'll have the scope to introduce new ideas, champion best practices, and contribute to the development of the organisation's wider data and technology landscape. There's also the opportunity to provide guidance to more junior team members and support the continuous improvement of analytics capability across the business.

What you can expect:
  • A varied role combining analytics, modelling, visualisation, and stakeholder engagement
  • Influence over the organisation's data and technology approach
  • The freedom to propose new methods, tools, and ways of working
  • Close collaboration with senior stakeholders
  • Hybrid working - 2 days a week onsite in Bristol
Technical experience we’re looking for:
  • SQL Server, Python, R, Power BI
  • Advanced analytics, predictive modelling & machine learning
  • Data visualisation and clear insight storytelling
  • Experience with Azure and awareness of emerging technologies, including AI
  • Ability to explain complex outputs to non-technical audiences

Due to the volume of applications received for positions, it will not be possible to respond to all applications and only applicants who are considered suitable for interview will be contacted.

Proactive Appointments Limited operates as an employment agency and employment business and is an equal opportunities organisation

We take our obligations to protect your personal data very seriously. Any information provided to us will be processed as detailed in our Privacy Notice, a copy of which can be found on our website


#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.