Data Quality Analyst

Hanson Lee
London
1 week ago
Applications closed

Related Jobs

View all jobs

Data Quality Analyst

Data Quality Analyst

Data Quality Analyst

Data Quality Analyst

Data Governance & Quality Analyst

Data Quality & Governance Analyst

A successful and established London Market syndicate is seeking a highly motivated and detail-oriented Data Quality Analyst to join their team. The Data Quality Analyst is integral to ensuring the organization's data assets are managed, secured, and utilized to support business decision-making.


As Data Quality Analyst will play a key role in maintaining and driving quality standards, policies, and procedures related to data governance while collaborating with stakeholders across departments to enhance data quality and integrity.


NB: If you do not have experience of working in the insurance sector, you will unfortunately NOT be eligible for this role.


Key Responsibilities:

  • Develop and implement a comprehensive data governance framework
  • Help create, implement, and maintain data governance policies and procedures to ensure the business is compliant with relevant regulatory requirements
  • Work with data owners and data stewards to establish and enforce data quality metrics, monitoring, and improvement processes
  • Identify and appoint data stewards, providing guidance and support
  • Develop and maintain a data catalog, taxonomy, and data lineage documentation
  • Advocate for data quality best practices and drive initiatives to enhance data-driven decision-making
  • Develop and deliver training and awareness programs to promote data governance & data quality principles across the organization


Experience Required:

  • Minimum of 3 years in data governance, data management, or a related field
  • Data Governance Expertise: Proven experience in developing and implementing data governance/quality policies and procedures in a regulated environment
  • Technology Skills: Familiarity with data management technologies and tools, such as data catalogues, data lineage, and data quality tools
  • Stakeholder Management: Proven history of working with both technical and non-technical stakeholders, bridging the gap between data teams and business units

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.

Jobs

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Jobs

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Jobs

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

🍪 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.