Data Scientist ID10945PA
2017-09-18 -> 2017-09-19
- Experience with multinational organization
- Online advertising experience - preferred
- Intermediate English Language ability
- A Degree in a mathematical, computational or physical science with strong machine learning component.
- Experience with machine learning frameworks such as scikit-learn, mahout, libsvm, MLlib (in Spark), torch, theano, tensorflow, etc.
- Strong background in Machine Learning, Data Mining, Artificial Intelligence, including but not limited to Bayesian networks, Neural networks, Heuristics, Support vector machines, genetic algorithms, or PAC learning, statistical classification techniques such as k means and hierarchical clustering, partition trees, and logistic regression.
- Strong experience in implementing large-scale data science pipeline, machine learning algorithms.
- Experience with visualization tools such as d3, matplotlib, ggplot…
- Experience in Large-Scale Database System, Distributed system (Google Big Query/Amazon Redshift, Hadoop/Mongo, Hive/Pig/SQL) is a PLUS
- Experience with one or more general purpose programming languages including but not limited to: Java, C/C++, Python, R, Scala, or Go.
- Help drive our Data Management Platform development. This will involve a wide range of extraction, analysis, and machine learning in a fast moving and flexible environment. You will be naturally analytical and apply this logic to create the best data management strategies within this project.
- Have a passion for engineering and optimising databases and algorithms which normalise, filter, reduce and process huge datasets of online transactions in a cost and performance effective manner to deliver highly valuable data outputs.
- Have strong mathematical and statistical background which will help you to conceive cutting edge solutions to riddles derived from business requirements, and script them in DB languages such as SQL.
- Have mixed qualities of being a perfectionist, and constantly looking to improve your algorithms, whilst knowing how to manage your task backlog well in order to meet tight, fast paced deadlines.