Data Sicence & Analytics Engineer

DeFacto Perakende Ticaret Anonim Şirketi

World of added values – DeFacto!

A Happiness Team which care about, solely work for your happiness… In other words +1 happiness!

A healthy life with a permanent sports trainer, fitness center and a quality life consultant… In other words +1 health!

If qualifications and basic functions we are looking for suit you, then come and Join DeFacto, come and bring +1 value to your life as well as ours and let’s Sprint to Future together! 

Qualifications:

·         Bachelors degree from a reputable universities (Engineering, MIS, Statistics, Mathematics etc.)

·         Minimum 4 years of experience in statistical analysis and research of large data sets, having Fast Fashion Retail experience is a plus.

·         Hands-on application experience of machine learning models, statistical methods and optimization algorithms in real-life problems

·         Experience in developing statistical models and proficiency in one of the statistical platforms such as  Python, R or SAS

·         Knowledge on predictive models and/or optimization techniques.

·         Experience in NoSQL (MongoDB, HBase, Elastic Search, Cauchbase etc.) and SQL databases

·         "Have basic understanding and willingness to learn below concepts:

o   Tensorflow, Scikit-learn, Spark ML or similar tools and frameworks.

o   Visualization tools, PowerBI, Tableau, QlikSense etc.

o   Google Analytics, Adjust, Firebase"

·         Experience with building and using models on cloud platforms (like AWS, Google Cloud) is a plus

·         Ability to plan, lead and execute a project end-to-end

·         Knowledge of agile methodologies such as Scrum or Kanban is a plus

·         Have outstanding organizational, interpersonal and communication skills.

·         No military obligation for male candidates 

Basic Functions:

·         Participate on different data science and optimization projects on different levels like design, model development, code construction and deployment.

·         Collect, understand and analyze all requirements and needs, design appropriate solutions and algorithms

·         Use analytical findings to create roadmap initiatives and create key metrics to evaluate and continuously track solution performance and health 

·         Model, code and solve Data Science and/or Operations Research problems.

·         Constantly improve skills and knowledge on machine learning techniques and data science tools.