Overview

Foodpairing® is a food tech company and a pioneer in digitization of food.

Foodpairing offers three products;

B2C: an app for personalized dietary recommendations (under development)
Chefs: inspiration for new flavor combinations
B2B: an AI platform for product development

Be part of the flavor revolution

Foodpairing is looking to strengthen its team with a mid-level or senior data scientist with NLP expertise. As a Data Scientist, you will report to the Lead Data Scientist and Chief Scientific Officer (Co-Founder). You will play a strategic role in the innovation, research and development of Foodpairing’s products for personalized food recommendations and consumer flavor intelligence (where you will be responsible for all NLP-oriented technology components.) You will also participate in time-boxed projects (internal and client) requiring NLP expertise. You will work from our analytical lab in Ghent.

The level of experience you have will determine the seniority level of the role offered. As a senior data scientist, you will also take up ownership of all internal NLP-based technology, and act as a project lead and coordinate the execution of internal and client projects.

Company:

Foodpairing

Qualifications:

Who are you?

You are a critical and strategic thinker with a fearless attitude. At the same time you are able to collaborate with others and adapt to the dynamic nature of the business.
A Masters degree (Computational Linguistics, Engineering, Physics, Computer Sciences,..) holder with 3+ years of experience as a (NLP) data scientist in an industry setting OR
A PhD (Computational Linguistics, Engineering, Physics, Computer Sciences,..) with 2+ years of experience as a (NLP) data scientist in an industry setting.
You have experience in technology development in an industry setting.
You have 3+ years experience in python in a data science context. Preferentially also in the area of algorithm development or software engineering.

Important skills to have:

Experience in NER, word embeddings, document classification.
Experience in training and validation of multi-layer neural networks and neural network architectures in the area of NLP.
Knowledge in the python package spaCy.
Experience in industry-standard python packages numpy, scipy, scikit-learn, pandas, keras, pytorch, matplotlib/plotly.

Bonus points for:

Knowledge in the other data science related disciplines, such as:
Feature engineering and ‘shallow’ learning techniques (e.g. random forests)
Clustering
Statistics
Dimensionality reduction.
Experience with cloud platforms, e.g. GCP, AWS.
Experience with Google AI Platform.
Experience with industry standard SQL or noSQl database technologies.
Experience with version control software tools, e.g. git.

Educational level:

Master Degree

Level of experience (years):

Mid Career (2+ years of experience)

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