We identify projects that will significantly impact your bottom line


We build a diversified portfolio of projects



We define clear candidates profiles that are needed to implement the strategy


We screen candidates and present you with a short list



We manage the team to implement the different models


We work with all stakeholders for a better collaboration


We choose data science projects for their potential impact on the company’s bottom line, and how well they complement each other. Diversification along axes like complexity, time horizon, and business lines is a must. This results in an optimal portfolio of projects that defines your data science strategy. This is very similar to what pharmaceutical firms do with their portfolio of R&D drugs.

Each project is clearly defined, identifying their goals, their potential impact, their risk profile, any operational constraints or goals, and the relevant data. It also helps, later in the process, hire the right talent, by specifying precise job descriptions. It becomes easier for data scientists to work on these projects.

We work with your human resources department and/or external recruiters to identify the candidates needed to implement this strategy. Our background positions us to identify the right profiles, hence reducing the time you spend to hire this team.

We first define the candidates profiles we need to implement our strategy. These obviously include some required technical skills, but also personality traits and learning abilities.

We then interview and test those candidates using a rigorous process, that can include both technical and psychological tests.

We manage the team to implement the models, and monitor their progress and the validity of the findings, during this research phase.

We involve all stakeholders very early in our process, with clear operationalization goals, which guarantees an optimal implementation of the data science products in your production environment.

We improve collaboration and communication between the business, the data science team and IT, hereby reducing the number of projects that fail. In a world where companies hire almost exclusively specialists, generalists are the missing piece required to bridge the gaps between the different business functions. As such, we speak the language of the business stakeholders, modelers and developers, thanks to our domain knowledge, modeling expertise, development skills and understanding of human behavior.