Data Product Lead

Cornhill, Greater London
2 weeks ago
Applications closed

Related Jobs

View all jobs

Product Data Scientist (Mid-level)

Head of Product Management

Quantitative Research - CDO Data Governance - Vice President

Senior Data Scientist

Senior Data Scientist - Commercial Analytics

Marketing Analyst

Data Product Lead  

London (Hybrid)

£85,000 - £105,000

We’re partnered with one of the UK’s leading brands that are currently hiring for a Data Product Lead. Our client is driven to be the best in the field and outdo with their experience in data and technology. The business has modified the work structure to help the customers, take on new technologies and develop business outclass.

The Data Product Lead will focus on the data and machine learning products and aim to drive the data strategy, development and delivery of the organisation. The position will benefit from hybrid working of 3 days a week onsite from their London office.

Responsibilities of the Data Product Lead:

Drive the Data Product strategy that aligns with the business data strategy and goals.
Collaborate with stakeholders at different levels to identify opportunities and make sure the product is launched successfully 
Own the full lifecycle of the data products, governance to maintain quality, integrity and consistency of the products
Track the data product performance to drive continuous improvement
Requirements of the Data Product Lead:

5+ years’ experience in Data product management with a background delivering data products
Experience managing and establishing governance 
Strong understanding of Azure products such as Databricks
Good background in Machine Learning (ML) analytics and deploying products 
Proven ability to mentor teams and lead continuous improvement in the data environment
Excellent communication skills, attention to detail and self-starter
To discuss this exciting opportunity in more detail, please APPLY NOW for a no obligation chat with your VIQU Consultant. Additionally, you can contact Katie Dark on  

If you know someone who would be ideal for this role, by way of showing our appreciation, VIQU is offering an introduction fee up to £1,000 once your referral has successfully started work with our client (terms apply).

To be the first to hear about other exciting opportunities, technology and recruitment news, please also follow us at ‘VIQU IT Recruitment’ on LinkedIn, and Twitter: @VIQU_UK

Data Product Lead  

London (Hybrid)

£85,000 - £105,000

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.

Jobs

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Jobs Careers

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Jobs

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.

🍪 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.