Hivemind is a software start-up based in the UK. We spun out from the data-driven global investment management company Winton Group in June 2018. Since then we have grown to be a team of 17, secured funding from Fidelity International and Barclays, been selected to be part of the Investment Association’s inaugural fintech accelerator, won the FIA Innovator of the Year 2019 award, and secured a range of clients from hedge funds and asset managers to data vendors and technology startups.
What we do
Hivemind offers specialist software to help our clients produce exceptional data sets. Our software is a low-code, human-in-the-loop solution that enables clients to generate clean, structured, analytics-ready data from unstructured, messy or incomplete sources. We believe that data science works best in partnership with human decision making; Hivemind was created, on this belief, to address the biggest challenge in data science which is getting great data.
Hivemind embeds human decision-making into data preparation workflows to provide a practical, flexible solution to data problems. Problems are broken down into a systematic assembly line of tasks that can be distributed to the most appropriate person, team, or computational method to resolve. Their responses are aggregated through comprehensive data quality processes into a final structured dataset.
With Hivemind, clients can build a competitive advantage by creating datasets exclusive to their organisation, save time and money by accelerating data preparation to bring products or research to market faster, and optimise their resources by reducing the amount of manual data wrangling in their expert teams.
Purpose of the role
Client Facing Data Scientists (CFDS) are critical to enabling our clients to use Hivemind successfully and our engineers to build a great product. They play a crucial role within the business sitting between our Sales and Engineering teams, and are heavily involved with both the sales process and product development.
On a day-to-day basis CFDS work side-by-side with the Sales team to help our customers achieve their goals with Hivemind. They do this as part of the sales cycle, as part of ongoing customer success, and sometimes through the delivery of data science projects on behalf of the customers. Internally, they act as the voice of the customer to our product engineers and help design and, when required, build data science solutions to be integrated into the product.
Roles and responsibilities:
An ideal candidate should have strong fundamentals of applied data science in a business setting, and should enjoy and have experience communicating the value of data science solutions to business and technical stakeholders. We are looking for candidates who can
demonstrate expertise in and an understanding of the importance of dataset creation, preparation and wrangling rather than those more focused on the development of machine learning models.
The main experience and personal characteristics we are looking for are:
It would also be advantageous to have any of the following: