Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Head of Data Science (Insurance)

Vallum Associates
City of London
1 week ago
Create job alert
Overview

(Hybrid)

Responsibilities
  1. Oversee the delivery of strategic data programmes, ensuring adherence to defined scope, budget, and quality standards.

  2. Work closely with Data Governance, Business and key stakeholders to drive the programme and roadmap of change.

  3. Monitor delivery progress, identifying and mitigating risks and issues as they arise.

  4. Prepare and present updates and reports to senior management and stakeholders, ensuring transparency and alignment with organizational objectives.

  5. Ensure compliance with organizational policies and best practices throughout the project lifecycle.

  6. Oversee appropriate resourcing, identifying key requirements needed from cross-functional teams and external vendors; sourcing and managing appropriate vendor partners.

  7. Ensuring deliveries align with the strategic vision and roadmap.

  8. Ensures compliance between business strategies, enterprise transformation activities and technology directions, setting strategies, policies, standards and practices.

  9. Responsible for effective and timely development of new and/or enhanced systems/technologies.

  10. Monitor all aspects of the Software Development Lifecycle and Production Support service levels, ensuring high-level technical support is provided for data-related technologies.

Role & Responsibilities
  1. Extensive knowledge of modern databases technologies, Snowflake and relational (such as Oracle, SQL Server and PostgreSQL)

  2. Broad knowledge of software development techniques, processes, methods and best practices. Proficiency with various programming languages.

  3. Strong leadership skills with the ability to motivate and guide teams towards successful project delivery.

  4. Excellent communication and interpersonal skills, capable of engaging effectively with stakeholders.

  5. Problem-Solving: Proactive and solution-oriented, with a keen ability to identify and resolve issues promptly.

  6. Knowledge of application test automation products, processes, and best practices

  7. Proven experience and strong understanding of Agile development and conventional method and its application to company technology needs.

  8. Strong strategic decision making & long-term planning abilities to manage resources and develop efficient and effective solutions to diverse and complex business problems.

  9. Good general business acumen.

  10. Experience with Insurance / Reinsurance Systems and Data.

  11. Knowledge of technologies such as Python, PowerBI.


#J-18808-Ljbffr

Related Jobs

View all jobs

Head of Data Science

Head of Data Science

Head of Data Science

Head of Data Science

Head of Data Science

Head Of Data Science

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.

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.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

Why the UK Could Be the World’s Next Data Science Jobs Hub

Data science is arguably the most transformative technological field of the 21st century. From powering artificial intelligence algorithms to enabling complex business decisions, data science is essential across sectors. As organisations leverage data more rapidly—from retailers predicting customer behaviour to health providers diagnosing conditions—demand for proficiency in data science continues to surge. The United Kingdom is particularly well-positioned to become a global data science jobs hub. With world-class universities, a strong tech sector, growing AI infrastructure, and supportive policy environments, the UK is poised for growth. This article delves into why the UK could emerge as a leading destination for data science careers, explores the job market’s current state, outlines future opportunities, highlights challenges, and charts what must happen to realise this vision.