Delivering AI is a team sport

An effective AI solution requires much more than a great data scientist. Product thinking, engineering and design are all key to ensuring the right problem is being solved, in a way that’s usable and reliable.

A DataSparQ team will typically have the following roles:

Product Manager

Our Product Managers maximise the impact of any intelligent product built by DataSparQ. They are laser-focused on identifying the value opportunity, and ensure the product built is delivering this value quickly and incrementally. They work with you to prioritise commercial and operational opportunities i and translate this into practical applications of data and analytics solutions. Day-to-day they are on point to lead our development activities (backlog management, sprint planning) and manage the communication and prioritisation with delivery teams.​

Applied Scientist

Our Applied Scientists are from strong academic backgrounds, all with PhDs – but they aren’t interested in just solving academic problems. They get to grips with the intricacies of a business problem to understand which algorithms are going to be the most appropriate. Sometimes it will be complex R&D techniques. Often it isn’t. Their analytics approach is practical, elegant, ethical and robust. All our applied scientists are strong coders (usually Python), and are familiar with distributed processing (they won’t build a model in R on a single VM if they know it’s not sustainable).

AI Engineer

Our AI Engineers come from a software engineering background, with a passion for big data and analytics. They are responsible for making sure the products we build are scalable, robust and efficient. They’re a crucial part of the team from day one on a project, working to ensure we’re always developing with production in mind. They’re passionate about the latest DevOps and CI/CD best-practices, efficiencies such as infrastructure-as-code and use the latest serverless components to minimise operational overheads. They work closely with the end users and system owners to make sure our ML models are embedded efficiently in daily workflows.​

Data Designer

Our Data Designers are responsible for building the interfaces and consumption endpoints for our algorithms. They combine a visual design and user experience design skillset, with an engineering discipline to build the end product. These might be workbooks in Tableau or PowerBI, or interactive interfaces on the web (using JavaScript frameworks such as Node.JS, or React) or mobile (using Vue or React native) or developing APIs (using Flask, Spring, Go) so that model outputs can be consumed programmatically. Our data designers are from an engineering background with experience in building products or digital experiences that gives them the UX appreciation and curiosity to design and build the most effective consumption endpoint that will drive adoption.

We’re a growing team of people who love combining business strategy, data science, engineering and design to create and build successful data science solutions and products. We’re always looking to bring in new people who can complement the team – head over to our linkedIn page to see our open positions.

Augmented intelligence, expertly engineered​

For any inquiries please email

Orion House, 5 Upper St Martin’s Lane
London WC2H 9EA