Senior Business Analyst, Data

City of London
3 days ago
Create job alert

Senior Business Analyst is sought by global and highly prestigious insurance group to join its fast-moving and cutting-edge data function. This role sits within a team responsible for driving data-led transformation, delivering scalable solutions and supporting business-wide strategy through insightful analysis and effective stakeholder engagement.

This role will see you working closely with senior stakeholders, technical teams, and delivery leads to define requirements, shape product visions, and influence the strategic direction of key data initiatives.

Key Responsibilities:

  • Define and own the product vision for data initiatives, ensuring alignment with business objectives.

  • Lead requirements-gathering sessions and translate complex needs into clearly defined deliverables.

  • Develop business cases, define Minimum Viable Products (MVPs), and prioritise features that deliver business value.

  • Collaborate with technical teams to design scalable and secure solutions using cloud-based data architectures (e.g. Azure, AWS, data lakes, data mesh).

  • Provide mentorship to junior and mid-level analysts, promoting best practice and continuous learning.

  • Support Agile delivery processes including sprint planning, backlog refinement, and retrospectives.

  • Conduct advanced data analysis to support business decision-making and identify areas for optimisation.

  • Ensure adherence to data governance, privacy, and compliance frameworks, particularly in regulated environments.

    Key Requirements:

  • Extensive experience in data-focused business analysis and product ownership within regulated industries.

  • Expertise in cloud platforms (Azure, AWS) and data architectures (e.g., data lakes, data mesh).

  • Proficiency in Agile methodologies and advanced tools like Jira and Confluence.

  • Strong leadership and communication skills, with the ability to influence cross-functional teams.

  • In-depth knowledge of data governance, privacy, and compliance standards.

  • Degree in Business, Computer Science, Finance, or a related discipline (desirable).

  • 5+ years’ experience in a Business Analyst role, with demonstrable leadership in data-driven projects.

  • Professional certifications such as BCS Business Analysis, ScrumMaster, or Agile Product Owner are highly advantageous.

    This role offers the opportunity to work in a collaborative, forward-thinking environment where data is central to business strategy. The organisation offers flexible working arrangements, ongoing development opportunities, and a strong focus on culture and values

Related Jobs

View all jobs

Senior Business Analyst - Insurance

Senior Business Analyst - Insurance Retail

Business Analyst - ITIL + Service Delivery

Business Applications Analyst & Project Manager

Business Analyst

Business Analyst

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Tips for Staying Inspired: How Data Science Pros Fuel Creativity and Innovation

Data science sits at the dynamic intersection of statistics, computer science, and domain expertise, driving powerful innovations in industries ranging from healthcare to finance, and from retail to robotics. Yet, the daily reality for many data scientists can be a far cry from starry-eyed talk of AI and machine learning transformations. Instead, it often involves endless data wrangling, model tuning, and scrutiny over metrics. Maintaining a sense of creativity in this environment can be an uphill battle. So, how do successful data scientists continue to dream big and innovate, even when dealing with the nitty-gritty of data pipelines, debugging code, or explaining results to stakeholders? Below, we outline ten practical strategies to help data analysts, machine learning engineers, and research scientists stay inspired and push their ideas further. Whether you’re just starting out or looking to reinvigorate a long-standing career, these pointers can help you find fresh sparks of motivation.

Top 10 Data Science Career Myths Debunked: Key Facts for Aspiring Professionals

Data science has become one of the most sought-after fields in the tech world, promising attractive salaries, cutting-edge projects, and the opportunity to shape decision-making in virtually every industry. From e-commerce recommendation engines to AI-powered medical diagnostics, data scientists are the force behind innovations that drive productivity and improve people’s lives. Yet, despite the demand and glamour often associated with this discipline, data science is also shrouded in misconceptions. Some believe you need a PhD in mathematics or statistics; others assume data science is exclusively about machine learning or coding. At DataScience-Jobs.co.uk, we’ve encountered a wide array of myths that can discourage talented individuals or mislead those exploring a data science career. This article aims to bust the top 10 data science career myths—providing clarity on what data scientists actually do and illuminating the true diversity and inclusiveness of this exciting field. Whether you’re a recent graduate, a professional looking to pivot, or simply curious about data science, read on to discover the reality behind the myths.

Global vs. Local: Comparing the UK Data Science Job Market to International Landscapes

How to evaluate salaries, opportunities, and work culture in data science across the UK, the US, Europe, and Asia Data science has proven to be more than a passing trend; it is now a foundational pillar of modern decision-making in virtually every industry—from healthcare and finance to retail and entertainment. As the volume of data grows exponentially, organisations urgently need professionals who can transform raw information into actionable insights. This high demand has sparked a wave of new opportunities for data scientists worldwide. In this article, we’ll compare the UK data science job market to those in the United States, Europe, and Asia. We’ll explore hiring trends, salary benchmarks, and cultural nuances to help you decide whether to focus your career locally or consider opportunities overseas or in fully remote roles. Whether you’re a fresh graduate looking for your first data science position, an experienced data professional pivoting from analytics, or a software engineer eager to break into machine learning, understanding the global data science landscape can be a game-changer. By the end of this overview, you’ll be better equipped to navigate the expanding world of data science—knowing which skills and certifications matter most, how salaries differ between regions, and what to expect from distinct work cultures. Let’s dive in.