Data Scientist, Natural Language Processing
40hr/Full-time - Rotterdam, Netherlands or Remote
The one who makes sense of big data
We create state of art models that interpret professional human-written text into structured data and create unique products using it.
We are looking for a Data Scientist, with hands-on experience in Natural Language Processing, to reshape a Multi-Billion Dollar industry.
Responsibilities:
- You’ll be responsible for the full ETL circle of a complex AI solution
- Improve and design NLP models for classification and named-entity recognition problems.
- Create a strategic roadmap for the company in the domain of data science.
- Identify required data for future data models and collaborate with the IT team to develop data collection services.
- Collect, clean, validate data, prepare it for training.
- Develop reliable models. Track and Improve output quality.
- Deploy models to fast and scalable APIs.
Minimum requirements:
- Minimum 3 years of experience in Neural Networks, minimum 1 year in NLP
- Good PyTorch skills (alternatively: Keras/Tensorflow)
- Good knowledge of Neural Networks: RNN and LSTM
- Good knowledge of Natural Language Processing
Preferred qualifications:
- Hands-on experience in Full Cycle of Modelling: from Data collection to Deployment into production
- Sound experience with Natural Language Processing: named entity recognition, sentiment analysis, text summary, text classification – that sort of things
- Preferred experience with Spark and Ensables
We offer:
- Potential to take a leading role in Data Science department
- Bureaucracy Free approach, flexibility in choosing Modern Technologies
- Grow with C Teleport in a rapidly expanding business
- Work in a talented & diverse team speaking 7 languages
- Work Remotely or in Rotterdam. NL (relocation is mandatory for the leading roles)
Application stages:
- CV Screening
- Questionnaire form
- Introductory interview
- Technical interview
- Job offer
Apply Now, we carefully consider all the candidates and keep data for the future better matching positions if the application was not accepted.