Data scientist at ForFarmers, what does that mean? Read Randy Rosink’s story

2-12-2020

Department: Next Level Innovation

"Days that have few appointments (my favourite days) are all about: DATA. On those days, I deal with projects."

On 1 May of this year, I started working at ForFarmers as a data scientist within the Next Level Innovation (NLI) team. An absolutely wonderful challenge! Next Level Innovation is key pillar in the Build to Grow strategy of ForFarmers.

Why did I accept this job? For the most part, it was the clear ambition of ForFarmers to be more data driven that made me switch from the nice and very dynamic profession of consultant to this position in which I focus entirely on ForFarmers' data and innovation issues.

Afbeelding: Randy Rosink_in-line

My background

Allow me to give you a brief outline of my background, because I’m sure you’re all wondering: how DO you become a data scientist? After studying commercial economics, I began working as a credit controller for Randstad, a temp agency, while continuing my Master's degree in Business Administration part-time. Later, I became a business intelligence consultant. This position allowed me to help many businesses with accessing, visualising and interpreting data.

DATA, data and more data

I'm often asked what exactly it is that I do as a data scientist. Days that have few appointments (my favourite days) are all about: DATA. On those days, I deal with projects such as optimising order allocation. This involves determining which mill is the best to produce an order in terms of logistics and production costs. We're also working on a project that helps to predict the best ordering moment: what would be the optimal moment for a customer to place a new order in accordance with the data. The objective here is to lower the number of rush orders.

Another project is the ‘Data Lake’ – a central location where all data is gathered and can be made accessible. I’m talking about sources such as: weather data, formulas, slaughter data, hatchery data, CRV data, sensor data (i.e. feeding stations) and so much more in the future. 
In short, there are still enough challenges to get my teeth into!