Head of Data Compliance

Copello
Southampton
1 month ago
Applications closed

Related Jobs

View all jobs

Head of Data Compliance

Head of Data Compliance

Head of Data Compliance

Data Quality & Systems Manager

Data Quality & Systems Manager

Data Quality Improvement Manager

Copello have partnered with an established Defence Engineering business in the recruitment of a Head of Data Compliance. This role can be based out of multiple locations on a hybrid basis.
This is a senior, influential role where you’ll own GDPR and data compliance across the business, manage data risk, and act as the trusted advisor to senior leadership on all matters relating to data protection and privacy.
What you’ll be doing:


  • Acting as the lead authority on data protection, privacy and data risk across the organisation

  • Developing and embedding data compliance strategy, policies and governance frameworks

  • Advising senior stakeholders and influencing decision-making across technical and non-technical teams

  • Leading data breach investigations and working closely with security teams on data and cyber risk

  • Overseeing DPIAs, privacy by design and regulatory documentation

  • Reviewing data protection aspects of contracts and third-party arrangements

What we’re looking for:


  • Proven experience leading data protection and privacy in a complex or regulated environment

  • Strong knowledge of GDPR, data protection legislation and best practice

  • Confidence working with senior stakeholders and influencing across functions

  • Excellent communication skills — able to translate complex risk into clear, practical guidance

  • A proactive, pragmatic and solutions-oriented mindset

  • Desirable: experience working in defence, national security or similarly sensitive / regulated sectors

Please note candidates must be eligible for SC Clearance for this position.
If you are interested, please get in touch with Ella

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.

Careers

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.

Jobs

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.

Education

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.