Data scientist

Are you familiar with at least two of the following topics: mathematics, Python, and machine learning? Are you eager to learn the remaining one and use it on a brand new, currently developed product? We are looking for machine learning engineers for smart fuel price optimisation. You will be able to participate on either of those projects or even on both of them. Quichesoft is young startup company, which is working on cutting edge applications. Enjoy working on them as a part of a multifunctional team. Each team consists of different roles, so there is big space to learn new things. You will be one of the first employees so your work will have huge impact on company! Join us if you want to play with latest technologies like machine learning and augmented reality. On top of that – we can discuss possibility of working for equity.

What you’ll do:

Work in team with other data scientist on a unique projects.
Turn your own ideas into prototypes and models. If you have an idea about new type of data or modelling approach you are encouraged to bring it to life. And we expect you to come with such ideas!
● Collect data from various sources, transform them into usable form and apply statistics, machine learning and microeconomics. You will be modelling demand for fuel.
● Develop a production tool that daily utilizes market data, makes predictions and maximizes profit of filling stations. Create analytical and visualization tool to support your predictions and help gas station operators to understand your models. (fuel price optimisation)

● Master’s degree in Mathematics, Economics or Computer Science preferred. Other fields accepted if candidate has exceptional skills.
● Understanding of common statistical tools and machine learning algorithms. You should be able to explain K-means algorithm, for example.
● Solid programming skills related to data processing and machine learning (Python / R / Scala).

Extra Points:
● Experience with applying machine learning models into microeconomics and/or financial markets.
● Skills in Keras and Tensorflow libraries.
● Experience from petroleum, retail or transportation industry. (fuel price optimisation)