- Masters degree in IT and minimum 13 years of experience (or Bachelors degree in IT and minimum 17 years of relevant experience).
- One of the following is recommended: Advanced university degree in NLP (computer science or computational linguistics) or A specialisation in (statistical/neural) machine translation (MT) or University degree in IT / Computer Science / Engineering or equivalent with specialisation in artificial intelligence.
- Excellent experience of Perl Python Matlab R and its NLP/ML libraries (SpaCy NLTK scikit-learn pandas ).
- Strong experience with ML techniques and algorithms such as k-NN Naive Bayes SVM Decision Forests Neural Network and AI frameworks.
- Experience in the field of corpus based linguistics and alignment models and classification methods.
- Experience with data analytics over big datasets non-structured databases as well as data lakes.
- Previous experience with Data Management Database Mining systems and in Big Data technologies.
- Experience with AWS and/or Azure Oracle RDBMS and PL-SQL.
- Previous exposure with Linux Unix Bash and scripting languages.
- Good knowledge of natural language processing systems lifecycle and agile software development methodologies.
- Good knowledge of quality assurance and quality control for machine translation (MT) and experience with MT quality procedures testing methodologies and tools such as automatic quality metrics (BLEU scores and similar) and human evaluation of MT quality.
- Some experience with query languages such as SQL Hive Pig etc.
- Knowledge of NoSQL databases such as MongoDB Cassandra HBase etc.
- Knowledge of data visualisation tools such as GGplot etc.
- Advanced English (C1) communication skills (written and spoken).
Desirable:
- Certification in AWS Certified Machine Learning or Microsoft Azure AI Engineer Associate or SAS Certified Professional AI and Machine Learning Certification.
Masters degree in IT and minimum 13 years of experience (or Bachelors degree in IT and minimum 17 years of relevant experience). One of the following is recommended: Advanced university degree in NLP (computer science or computational linguistics) or A specialisation in (statistical/neural) machine...
- Masters degree in IT and minimum 13 years of experience (or Bachelors degree in IT and minimum 17 years of relevant experience).
- One of the following is recommended: Advanced university degree in NLP (computer science or computational linguistics) or A specialisation in (statistical/neural) machine translation (MT) or University degree in IT / Computer Science / Engineering or equivalent with specialisation in artificial intelligence.
- Excellent experience of Perl Python Matlab R and its NLP/ML libraries (SpaCy NLTK scikit-learn pandas ).
- Strong experience with ML techniques and algorithms such as k-NN Naive Bayes SVM Decision Forests Neural Network and AI frameworks.
- Experience in the field of corpus based linguistics and alignment models and classification methods.
- Experience with data analytics over big datasets non-structured databases as well as data lakes.
- Previous experience with Data Management Database Mining systems and in Big Data technologies.
- Experience with AWS and/or Azure Oracle RDBMS and PL-SQL.
- Previous exposure with Linux Unix Bash and scripting languages.
- Good knowledge of natural language processing systems lifecycle and agile software development methodologies.
- Good knowledge of quality assurance and quality control for machine translation (MT) and experience with MT quality procedures testing methodologies and tools such as automatic quality metrics (BLEU scores and similar) and human evaluation of MT quality.
- Some experience with query languages such as SQL Hive Pig etc.
- Knowledge of NoSQL databases such as MongoDB Cassandra HBase etc.
- Knowledge of data visualisation tools such as GGplot etc.
- Advanced English (C1) communication skills (written and spoken).
Desirable:
- Certification in AWS Certified Machine Learning or Microsoft Azure AI Engineer Associate or SAS Certified Professional AI and Machine Learning Certification.
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