At Intelygenz, we envision a future where processes accelerate performance. For the companies we work with, this means finding ways to optimize their data using cutting-edge technologies like AI-enabled automation. This mindset is a huge part of our culture. We thrive on pooling our skills, collaborating on projects, helping one another learn and creating innovations.
What are you going to do?As a data scientist at Intelygenz, your day-to-day work will be organized in two principal lines: Industry and Laboratory.
At the Industry level, our main delivery is process automation. Our artificial intelligence solutions are focused on automating processes to add business value to our customers. This approach is applied in many different business sectors from NLP-based projects and advanced computer vision to multi-domain anomaly detection. A crucial step in the industrial process is the deployment of production-ready environments, their monitoring and maintenance.
On the other hand, the goal of our Laboratory is to research and test state-of-the-art techniques and solutions to keep improving our skills and to share with the community our knowledge and proof of concepts. Deep reinforcement learning, NLP revolutionary solutions (as Transformers or BERT) or Brain-Computer-Interface experiments are some examples of our active research lines.
What will make you succeed in your role?Demonstrable knowledge of Mathematics and Statistics.Minimum of two years experience in working on data-based projects.Large experience with Python 3.Experience with cleaning tools and techniques, and data pre-processing.Experience with libraries and frameworks like Numpy, Pandas, Scikit-learn, PyTorch/Tensorflow.Machine Learning knowledge.English Professional Competency.Strong self-taught and proactivity capabilities.Problem-solving and autonomy when facing new challenges.Bonus Points:Have Computer Science background.Masters degree in Data Science or Artificial Intelligence.Experience applying state-of-the-art Artificial Intelligence techniques.Large experience in software projects beyond data science.
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