About the project
The data scientist works closely with solution consultant and solution owner to advise and jointly brainstorm on how Artificial Intelligence and Machine Learning can assist in larger problem solving. The data scientist covers the blending of historical data from available customer network data sources, public information, field reports, or purchased sources for building efficient algorithms. He/she uses the latest technologies and techniques which also comprises deep insight and knowledge in predictive analytics. Works in straight collaboration with software engineers and data engineers for integrating artificial intelligence and machine learning based algorithms in industrial products.
The Data Scientist must be prepared to work in a very dynamic environment that includes regular interactions with several organizations. He/she must be able to communicate effectively and have detailed knowledge of data preparation and cleansing, algorithm selection and design, results analysis and industrialization. The Data Scientist is solution-oriented, curious, open-minded, autonomous and willing to work in a team.
The position involves in-depth operational research on analytical issues, natural language processing, recognition of similarities, computer vision, optimisation algorithms, design and maintenance of artificial intelligence solutions, business acumen to suggest AI projects based on relevant data from the business.
- managing AI/ML projects starting with discovery phase, proof of concept, industrialization and deployment
- managing and supervises junior Data Scientists to define the methodology and evaluate the possible and most appropriate technical solutions
- leading the functional and technical analysis of the needs of internal and external customers in terms of analysis and contributes to the design and implementation of the customer solution
- describing, explaining and documenting the implemented solution as well as the results in terms of data analysis and solution performance
- proposing, implementing, testing and selecting the best machine learning algorithms using the different statistical tools and methodologies of Data Scientists to discover, describe and predict
- participating in the specification of industrialization and the implementation of the industrialized solution
- experience in the field of Data Science
- Machine Learning: supervised and unsupervised learning, linear and logistic regressions, random forests, gradient boosting, neural networks (RNN, LSTM, CNN), text mining and topics extraction, NLP, K-Means, decision trees, ML applied to computer vision
- Deep Knowledge of Python (sklearn, panda, numpy,..), Jupyter, Spark/Scala or R data science libraries, PostgreSQL, ELK, Java, Kubernetes, Docker, micro-services oriented architecture, collaborative tools (GitLab)
- Excellent English
- Master’s Degree or PhD in Statistics, Machine Learning, Data Science, Computer Science, Computer Engineering
- Machine Learning
- Python (sklearn, panda, numpy,..)
- upyter, Spark/Scala, R data science libraries
- micro-services oriented architecture
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