Senior Data Product Manager

Northampton
5 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Developer

Senior Data Scientist - Commercial Analytics London

Senior Data Scientist – Cardiff, London, or Remote (UK) | Visa Sponsorship Available | Monzo

Senior Data Scientist – Cardiff, London, or Remote (UK) | Visa Sponsorship Available | Monzo

Data Science Manager

High Salary! Senior Data Scientist - Relay Network

Step into the role of a Senior Data Product Manager at Barclays, where you'll drive the development of key data products, working with business owners to capture the key priorities and shape the problem statement into a clear backlog of ready work for the feature team. Define the roadmap for given data products, prioritising backlog and ensuring deliverables meet the definition of done. The purpose of this role is to ollaborate with product owners and other technical teams involved in the product development process and utilise their knowledge of the bank’s technologies to enact the vision defined in the product roadmap.

To be successful in this role you should have experience with:

Data & Analytics

Requirements Analysis

Senior Stakeholder Management

Working towards large scale deliverables

Agile Methodology

Some other highly valued skills may include:

Technical background with Data Engineer, Data Warehousing and Data Governance

Change and Transformation

You may be assessed on key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen, strategic thinking and digital and technology, as well as job specific technical skills

This role may be based out of Northampton or Knutsford.

Purpose of the role

To collaborate with product owners and other technical teams involved in the product development process and utilise their knowledge of the bank’s technologies to enact the vision defined in the product roadmap. 

Accountabilities

Provision of subject matter expertise to support the collaboration between the product owner and the technical side of product development.

Support the development and implementation of the product strategy and vision defined in the product roadmap and communicate them with the relevant stakeholders and the development team.

Collaboration with internal stakeholders to gather and prioritise product requirements and features based on business value and feasibility that are well defined, measurable and secure.

Development and implementation of assessments to ensure continuous testing and improvement of product quality and performance.

Monitoring of product performance to identify opportunities for optimisation that meets the banks performance standards.

Stay abreast of the latest industry technology trends and technologies, to evaluate and adopt new approaches to improve product development and delivery.

Vice President Expectations

Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment.

Manage and mitigate risks through assessment, in support of the control and governance agenda.

Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does.

Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business.

Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies.

Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions.

Adopt and include the outcomes of extensive research in problem solving processes.

Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes.

All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave

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.

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.