Entrepreneurial Data Scientists with specific domain or application knowledge
With our thorough screening process, we aim to get the top 20% of Data Science professionals in our platform. We want you to be able to work with highly motivated and passionate professionals that help your organization accelerate in the field of Data Science & AI.
Our function scope
Data professionals cover a wide spectrum of skills. In some cases, Data professionals are demanded to act and think with the business of your organization and work in an fast and agile way (build, learn, change). In other cases, a data professional can be asked to focus on a specific application for a longer time. Depending on your needs, you are able to search for Data professionals with specific technological skills, social or domain knowledge.
The Data Scientist mostly uses statistical techniques and creates (self learning) models that produce predictive information for a specific application. F.e.: a recommender system.
The Data Engineer uses engineering techniques to connect different data sources and creates a sustainable structure to collect and structure data on large scale.
The Data Architect uses engineering techniques to create a sustainable data infrastructure that works autonomously.
Machine Learning Engineer
A Machine Learning Engineer is specialized in self learning algoritmes.
A Product Owner is a experienced former data scientist/engineer/architect who can steer a project on a technical perspective. He or she sets out the technical vision of the project and makes sure all team members work together.
A Project Manager is less technical and more business orientated. He or she is the alignement between a data science team and a business manager or the management team.
A UX Designer emphasizes with the problem owner (business manager) and is able to design the userface/dashboard of the solution that is needed.
An Adoption Manager makes sure the company gets along with the new data science strategy. He or she organizes events/workshop to increase to overall knowledge and adoption of AI.
The Analytics Translator is the translator of business demands and data science opportunities. He or she has sufficient technical and business knowledge.