At Datasparq, we work a little differently with our Data Science recruitment. If you have a great skill set and track record in working on data science and optimisation projects, 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 in Data Science; get into new areas of data science; help you inspire others to success; and develop impact from landed Data Science projects. We want you to bring your teammates with you on that journey so we all get to benefit from the joint endeavour.

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

A Senior Data Scientist should have:

• [Client] A track record of demonstrated value/impact to business through Data Science investigation and projects
• [Client] Some project leadership experience with agile Data Science methodologies with Data Science or Optimisation-flavoured projects
• [Communication] Ability to effectively communicate their technical/process ideas at a company level (e.g. at chats, seminars)
• [Technical] Substantial experience with Data Science and Optimisation-oriented projects and investigations
• [Technical] A high quality quantitative first and second degree with good evidence of exploratory investigation in industry or academia usually around optimisation or operations research
• [Technical] Expertise in several Data Science/Mathematical optimisation tools or techniques that they are known for within their company/university (e.g in exact methods or heuristic generation)
• [Technical] A willingness to pursue professional accreditation with one of the core learned bodies around Data Science, Mathematics, OR, Statistics or Computer Science

We would look for a Senior in our team to have a selection (not all) of these attributes already or be more than willing to engage in these once they arrive.

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A Senior Data Scientist should expect to be:

• [Client] Responsible for a client project workstream, and manages delivery not just of themselves, but also supporting the rest of the team
• [Client] Demonstrating good client engagement, project management and expectation management
• [Client] Able to demonstrate a good portfolio of project achievements and learnings that have helped to shape the company technically and/or culturally
• [Communication] Starting to present externally to clients, in meet-ups and industrial gatherings.
• [Communication] Able to define workstream approaches, regularly inputs to staffing requirements and new business proposals
• [Communication] Able to participate actively in and helps to shape hiring processes within the company
• [Colleague] Willing to have line management responsibility and can demonstrate effective people management skills through this
• [Colleague] Able to show that they have team or small project leadership responsibility and can demonstrate effective people management skills through this 
• [Colleague] Able to motivate and help support a learning culture within Data Science and is leading by example‍
• [Colleague] Able to demonstrate ad hoc support of colleagues in projects (not necessarily ones they are working in) which better enabled the project to succeed

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.