Data Scientist

GBS
Manchester
5 days ago
Create job alert
Salary : £48,000-£53,000

JOB TITLE: Data Scientist


BUSINESS FUNCTION/ SUB-FUNCTION: Data and Information
LOCATION: London, Birmingham, Manchester, Leeds

Please note this role is not eligible for visa sponsorship.


role Purpose

The Data Scientist with significant expertise who will support the reporting and data-led decision-making for student and staff data. You will have experience in using techniques such as machine learning and artificial intelligence to build powerful data products that enhance decision-making throughout our organisation. You will use your business acumen to understand our sector and business goals and discover opportunities where data science can have a positive impact.


As a great communicator, you’ll translate complex scientific and statistical techniques into compelling visions for organisational improvement. As a data scientist, you’ll develop high-quality code and algorithms within GBS’s data and analytics platform. You’ll integrate them into business processes and day-to-day decision making.


ROLE And RESPONSIBILITIES

  • Work closely with stakeholders within our university to understand their objectives. Use your expertise to identify opportunities where data science approaches can support our organisation.
  • Use a scientific approach to solve challenges that face GBS. Provide scientific data products to improve student outcomes, the student experience, and operational efficiency.
  • Build and fine-tune machine learning models. Adopt a culture of continuous improvement measuring and improving results through evaluation of the effectiveness of the models.
  • Effectively communicate findings to a range of stakeholders, including providing actionable insights that drive decision-making.
  • Work closely with the Data Quality Manager and system owners to ensure the data is accurate and timely.
  • Adhere to our information security policies and ensure that you protect the use of our data within your algorithms.

ESSENTIAL SKILLS And EXPERIENCE

  • Experience delivering data-science solutions for large data sets.
  • Experience in programming language such as Python, R and SQL.
  • A strong understanding of Data Science techniques, including ML algorithms and statistical methods.
  • Proficient in building ML pipelines with Python.
  • A knowledge of sampling techniques and their implications for analysis.
  • Drives and encourages the practice of continuous improvement and organisational change; positively embraces change and draws out new ideas, opportunities, and solutions.
  • Ability to analyse and report on key performance indicators across complex and disparate data sets.
  • Demonstrated experience in creating business value using data & analytics.
  • An enthusiasm for engaging with non-technical stakeholders and establishing best practice processes.

Key Result Areas

  • Stakeholder Engagement & Requirements Gathering

    • High stakeholder satisfaction from business units (registry, IT, Academic Services).
    • Clear and validated requirements.


  • Knowledge Transfer & Documentation

    • Comprehensive technical documentation delivered for all designed components.


  • Data Quality & Data Security

    • Proactive identification and mitigation of technical and compliance risks.
    • No major security incidents linked to architectural design.
    • Adherence to data protection best practices and institutional IT policies.



Other Information

The Data Scientist will also be expected to demonstrate their commitment:



  • to GBS values and regulations, including equal opportunities policy.
  • to GBS’s Social, Economic and Environmental responsibilities and minimise environmental impact in the performance of the role and actively contribute to the delivery of GBS’s Environmental Policy.
  • to their Health and Safety responsibilities to ensure their contribution to a safe and secure working environment for staff, students, and other visitors to the campus.

This job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee. Other duties, responsibilities and activities may change or be assigned.


#J-18808-Ljbffr

Related Jobs

View all jobs

Data Scientist

Data Scientist

Data Scientist

Data Scientist

Data Scientist (Government)

Data Scientist - Renewable Energy

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.