Datasparq Product Leads…

• are organised, pragmatic, and action-oriented
• love working in multidisciplinary teams alongside engineers, data scientists and sales and marketing teams
• believe in agile, incremental delivery to ensure value is being delivered at every step
• try new things, evaluate, and stick with what works, sharing and promoting their learnings with colleagues
• are excellent communicators and comfortable engaging with clients
• are curious and questioning, they identify gaps before they become issues
• are value-focused and always looking to deliver products and solutions which solve real customer problems
• are passionate about the potential of AI/ML to create a positive impact.
• are obsessed with User Experience and ensuring that products are used and loved by customers
• have a good base of understanding of data and machine learning.
• can articulate a vision for a product they look after and can cut through the noise of requirements and feature requests to zone in on what’s important.
• have worked in great teams before, and know how to nurture a culture which delivers real value, quickly.

Datasparq Product Leads…

• lead development activities using agile methodologies including owning and prioritising the product backlog.
• build and maintain positive client relationships from pre-sales through to delivery and managed service.
• develop project proposals, assessing client opportunities and challenges through interviews and data analysis to develop cohesive AI/ML propositions
• contribute to “SparQshops™”, our unique discovery workshop designed to identify, qualify and validate AI opportunities.
• contribute to product strategy, working closely with their colleagues in the Product Management team.

Typically a Product Lead will have experience in some or all of the following:

• use of agile delivery tools such as Jira/Confluence.
• as an agile delivery lead (scrum master/project manager) responsible for running day to day delivery for a multidisciplinary team including software engineers and data scientists.
• supporting the rollout of new products or services with clients/customers, helping to manage any cultural or business change to ensure they deliver the value promised.
• as a Product Owner in an agile delivery team
• as an engagement lead in a professional services company, responsible for leading client relationships and ensuring agreed scope is delivered on time and budget.
• working in a product, delivery, or technical role which leans heavily on data, machine learning or AI.

Datasparq is a specialist AI & data firm that designs, builds and runs high-impact AI & data solutions. We build bespoke AI and data science tools—and turn them into robust, reliable services for our clients.

We are a highly dedicated team of experienced data scientists, engineers, product designers and visualisation professionals who between us solve impactful problems for a diverse range of companies from international airlines to multinational pharmaceutical companies to luxury global hotel brands. 

We start with research and iterate—using lean startup principles—to quickly uncover impactful solutions to high-value challenges. Our product team ensure that we build the right solution in the right way. Our data science team ensure that the AI and data science solutions we build are best-in-class. And, our engineering team ensure that solutions are robust and ready to be deployed in the real world. When it comes to operationalising solutions, we run data science products in the cloud as services for our clients or deploy to their infrastructure as needed.

We don’t just build ML models—we take our science from the broad spectrum of mathematics, statistics, operations research and computer science. We work with academic partners and Centres for Doctoral Training (CDTs) across the UK to ensure that what we do is founded on high-quality, up-to-date science.

As a company, we don’t just value diversity - we place it at the heart of what we do. We need diverse thinking from diverse people to help us create solutions quickly that are effective and respect the audience for the tool.