QUALIFICATIONS AND JOB DESCRIPTION
ETIYA is a global technology company with more than 900 employees in 3 continents, developing AI-driven digital transformation applications, based on international standards and customer experience.
ETIYA strengthens data-driven decision-making structures of organizations and helps them to take effective and agile actions by enabling all steps of the customer journey to be monitored and managed.
ETIYA, which prioritizes organizations’ transition to customer value management; utilizes its capabilities of Artificial Intelligence, Data Analytics and Customer Management as a competition leverage and enables them to build a full-digital and sustainable business model.
Having offices in the Netherlands, Canada, USA, Turkey, Ukraine, Singapore, UAE, ETIYA’s products and solutions have been awarded by independent organizations worldwide.
ETIYA, grounding on the corporate values by focusing on continuous innovation and improvement, aims its employees to exceed every day.
If you are
- an innovative
- an agile
- a bold DAYDREAMER
who is willing to contribute in a leading TECHNOLOGY company,
- passionate about INNOVATION
- oriented with AGILITY
- fed with COURAGE
we are looking forward to your application!
THE GENERAL QUALIFICATIONS OF THIS POSITION INCLUDE THE FOLLOWINGS:
- BS or MS in Statistics, Mathematics, Computer Engineering, Mathematical Engineering or related fields
Experience / Technical Knowledge:
- Minimum 2 years of related job experience
- Proficiency in at least one of R or Python
- Experience in statistical packages and ML libraries such as Python SciKit, R Caret etc.
- Interested in data analysis, modelling, segmentation, forecasting, churn analysis, recommendation system
- Having experience/knowledge about Amazon Web Services is a plus
- Good command of written and spoken English; since the new joiner may be positioned in an international project
- Innovative, agile and a collaborative team player
The successful new joiner will be a member of a strong team in local and international projects, which enables him/her to improve his/her technical and personal competencies.
He/she will be responsible for:
- Analyzing historical data and creating insightful data visualizations
- Building machine-learning/predictive algorithms such as regression, decision trees, random forests, support vector machines, gradient boosting etc.
- Making necessary developments for the automation of models on cloud (AWS)