Expert in AI/NLP/ML

• Development and maintenance of software applications in the field of Natural Language Processing (NLP), Machine Learning (ML) and/or Artificial Intelligence (AI); • Training of custom machine learning / deep learning models based on structured and unstructured data; • Selecting features, building and optimizing classifiers using machine learning techniques; • Studies and developments aiming at improving the quality of machine translation (MT) engines for each installed language pair, addressing the specific needs of customers of the service concerning MT quality and contributing to a general strategy for the systematic evaluation and long-term improvement of MT quality; • Interact with data stewards and other IT stakeholders to define the data rules; 1/4• Define data controls and implement actions to ensure data quality and integrity; • Creating automated anomaly detection systems and constant tracking of its performance; • Data mining using state-of-the-art methods; • Processing, cleansing, and verifying the integrity of data used for analysis; • Design the IT architecture for solitons in the NLP / ML / AI fields, and coordinate its implementation considering master- and meta-data management concepts; • Analyse data architecture for consistency, completeness, accuracy and reasonableness; • Contributing for the analysis of data management vision, strategy and policy and derive the IT requirements; • Contributing to the design of the IT architecture considering master- and meta-data management concepts; • Provision of expert advice and assistance in any area associated with the Artificial Intelligence and Data Warehouse technologies; • Perform design, development and maintenance of BI and reporting software that both follow the reference architecture rules and accurately implement the specifications received in the documents of analysis provided by the business analysts of the project; • Assistance and support to the Advanced Analytics developers; • Provision of technical studies, technical expertise, technical evaluations in relation with AI systems; • Depending on the circumstances, the expert may be requested to provide assistance or support in the resolution of production issues. 3. LEVEL OF EDUCATION Master Degree A specialisation in (statistical/neural) machine translation (MT), or equivalent experience. University degree in IT / Computer Science / Engineering or equivalent with specialisation in artificial intelligence. 4. KNOWLEDGE AND SKILLS Following skills and knowledge are required for the performance of the above listed tasks: • Excellent knowledge of Perl, Python, Matlab, R and its NLP/ML libraries (SpaCy, NLTK, scikit-learn, pandas...); • Excellent knowledge of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, Neural Network, and/or artificial intelligence frameworks; • Excellent knowledge of Data Management; • Good knowledge of AWS and/or Azure; • Good knowledge of Linux; • Good knowledge of Unix and Bash; • 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; • Knowledge of query languages, such as SQL, Hive, Pig, etc and with information extraction; 2/4• Knowledge of NoSQL databases, such as MongoDB, Cassandra, HBase, etc.; • Knowledge of data visualisation tools, such as D3.js, GGplot, etc; • Experience in the field of corpus based linguistics; • Experience with alignment models and classification methods; • Experience with data analytics over big datasets, non-structured databases as well as data lakes; • Good applied statistics skills, such as distributions, statistical testing, regression, etc; • Good scripting and programming skills; • Data-driven mindset; • Deep knowledge in Database Mining systems and in Big Data technologies; • Deep knowledge in Artificial Intelligence; • Working experience with Oracle RDBMS and PL-SQL; • Capacity to write clear and structured technical documents.