Please, bear in mind that this is a Paternity coverage initially.
We are EA
EA inspires the world to play, and the Worldwide Localization Team makes that happen! We are accountable for delivering the high-quality localized versions of our titles to over 30 countries around the world. You will find a vibrant, multicultural environment with a great mixture of professionals. From software engineers, project managers, testers to audio, text and linguistic specialists, each employee has an important role to play. EA has built a cutting-edge Localization powerhouse that covers the needs for both current and next-generation platform.
We are hiring a Data Science for our Localization Data & AI team. Loc Data & AI´s mission is to support and foster the use of data from all perspectives, along with developing policies and procedures for the monitoring and active management of data in EA Localization.
This includes an understanding of data extraction, transformation, and loading (ETL) techniques.
Design, develop, test and deploy Data Science and AI solutions.
Participate in the design, development, evaluation, deployment of data-driven machine-learned (ML) models targeting NLU and ER applications.
Create visualizations and reports of the results.
Support teams and individuals across the business in identifying impactful opportunities for advanced analytics.
Communicate outcomes to various project stakeholders, including senior management.
Own, improve and promote best practices and scientific methods for ML, advanced statistics and predictive modeling.
6+ years of industry work experience analyzing large datasets
A Bachelor's degree in Engineering, Computer Science, Math, Statistics or similar.
Advanced knowledge of Data Science, the available algorithms and how to implement them.
Knowledgeable with Data Science tools and frameworks (i.e. Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark)
Strong familiarity with Machine learning and Deep learning methodologies. Experience and/or motivation to work on modern Deep Learning approaches to NLP: text classification, domain-specific models.
Experience in NLP/NLU. Experience with NLP libraries such as NLTK, openNLP, Stanford-NLP, WordNet, SAS Text Miner or other NLP software.
Knowledge of data query and data processing tools (i.e. SQL)
Experience with GPU acceleration
Knowledge of Web App development.
Experience with integrating applications and platforms with cloud technologies (AWS and Azure)
Knowledge of external data available in the market and the different vendors.
Interest in reading academic papers and trying to implement state-of-the-art experimental systems
Excellent writing and communication skills in English.
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