At Datasparq, we work a little differently with our recruitment. If you have a great track record, then we want to help you get onboard with us. We will tell you what we’re looking for; we will give you guidance on how to make the most of your application during the process. We want you to succeed in getting the role and then we want to help you to excel in the role itself. We want to help you develop your career; help you inspire others to success; and develop impact from landed data projects. We want you to bring your teammates with you on that journey so we all get to benefit from the joint endeavour.

Most of all we want you to enjoy what you do and further enthuse the team with that enjoyment!

Consultant Data Analyst Role Ethos: Bringing the best of the team.

A Consultant Data Analyst must have:

• The ability to tell a story with data - to know what matters to the audience and understand which data should be presented in what way to create a compelling narrative.
• A track record of delivering value/impact to businesses through Data investigations and projects
• Ability to effectively present and communicate their technical/process ideas internally (e.g. at chats, seminars) and externally to clients, or in meet-ups and industrial gatherings.
• Experience designing visual interfaces and customer experiences (both data-oriented)
• Experience delivering data-oriented projects and investigations
• Experience with data visualisation toolkits, e.g. Tableau or PowerBI (Python desirable but not required)
• Experience in developing models and transformations with data query language: SQL
• Experience working with cloud architecture such as GCP, Databricks, AWS (desirable but not required)

A Consultant Data Analyst should expect to:

• demonstrate good client engagement, project management and expectation management
• help shape the company technically and/or culturally through a portfolio of project achievements and learnings
• Help define workstream approaches
• present externally to clients, in meet-ups and industrial gatherings.
• motivate and help support a learning culture within Data Analysis and lead by example

Datasparq is a boutique AI & data firm that solves complex business challenges.

We build bespoke AI and data science tools—and turn them into robust, reliable services for our clients.

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.

But—what’s special about Datasparq is the way our teams work together.

Just as no business challenge fits neatly into a box, neither do our people. Rather than simply hiring a data scientist or a data engineer, we seek out passionate experts who can bring a range of overlapping skills to any team. That gives us the ability to build the perfect team to solve any challenge. We believe in bespoke over one-size-fits-all.

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.

When it comes to operationalising solutions, we can run data science products in the cloud as services for our clients—or deploy to their infrastructure as needed.

Diversity & ethics

As a company, we don’t just value diversity—we place it at the heart of what we do. To create solutions that serve our users—and our clients' users—diversity is a must, not a nice to have. Likewise, we place ethics at the heart of what we do. Our team are passionate about working on projects that drive positive results for people and the planet. We routinely undertake ethics reviews and champion a culture of openness, honesty and integrity.