Be our new Data Scientist (Student position)
Precis is looking for a Data Scientist (Student position) to work from our office in Aarhus, starting approximately August 2019.
As a part-time Data Scientist at Precis, you will be working together with a team of highly skilled colleagues, but also work independently on complex marketing problems and unveil actionable results through complex data sets. From bidding algorithms to econometric modelling, you will explore and develop state-of-the-art machine learning techniques to help multinational companies who are eager to take their data-driven marketing to the next level. You will combine data analytics and business insights to build an information advantage for the clients you work with. Your understanding of data technology will help clients to consolidate, understand, and action the information they have at their disposal to optimise their digital investments.
This role is geared towards people who are excited to see what they can achieve in an environment where furthering our knowledge and trying new things is seen as a segue to breaking new ground. If you fit the part, you will be working in a fast growing organisation together with some of the most talented people in the industry.
This is a part-time student position and we expect you to have a minimum one year left of studies and you need to be able to work from the Aarhus office.
TASK & RESPONSIBILITIES
Collect data, build models, extract actionable results, and prepare presentations.
Specifically, you’ll help expand our portfolio of processes and tools surrounding Google Shopping and product feed-based work.
Helping clients to understand the effect of their marketing activities.
Strive to learn and master the latest technologies and techniques continuously.
You are interested in working with data-driven marketing, in an industry that is in constant development.
Proven analytical problem-solving skills.
Some experience working with large datasets.
Knowledge of SQL and good coding skills in Python or R.
Education within the quantitative field such as mathematics, statistics, machine learning, optimization, nonlinear modelling or similar.
Your first day!