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COM4U1:
Position title: Software engineer python/scikit-learn – Digital ads - time series predictions and supervised learning
Location: Data Science and Mining group, LIX, Ecole Polytechnique, France. More information: http://www.lix.polytechnique.fr/dascim/
Starting date: As soon as possible..
Duration: 12-15 months (Full-time)
Salary: Very good, depending on the candidate’s experience
Description:
The context of the project is the effect of digital TV advertising on website traffic. The objective is predicting the change in traffic on the website of the advertiser after the TV ad placement. A machine-learning model needs to be trained based on available data. Also we would like to study the effect of digital ad campaigns on the behavior of users. Apart from the software development aspect, this position has a certain academic flavor and can be a prelude to a further collaboration with the lab.
Required skills
- Bachelors degree (at least 4 years of Univ. studies) in Applied Math, Computers Science or Engineering; A Masters degree is a plus
- Experience in Python programming
- Understanding of code versioning tools (e.g. Git, SVN)
- Understanding of distributed ML with SPARK
- Good understanding of time series algorithms and machine learning in general
Desired skills:
- Ability to write reusable libraries
- Ability to work independently
- Good communication skills
- Very good knowledge of English language
Interested candidates are invited to send by email (Subject: COM4U1 – Software Engineer Position):
- their full CV with
- a motivation letter
to Prof. Michalis Vazirgiannis (michalis.vazirgiannis@gmail.com)
TENC1:
Position title: Software engineer – Large Scale graph mining
When: As soon as possible..
Duration: 12 months with very good remuneration
Description:
The context of the project is the application of state of the art graph mining algorithms (i.e. community detection, dense subgraph discovery) on large scale graph from the social networks industry aiming at: identification of high quality communities, b. predicting their structure and conducting graph classification based on innovative graph kernels. This work has apart from the programming part a certain academic flavor and can be a prelude to a further collaboration with the lab.
Required skills
- Master (min 4 years of Univ. studies) in Applied Math, Computers Science or Engineering b. very good understanding of linear algebra, optimization, graph algorithms c. experience in python programming d. understanding of distributed Machine Learning with SPARK e. understanding of code versioning tools (e.g. Git, SVN), e. solid understanding of the entire software development lifecycle f. ability to work independently g. good communication skills h. very good knowledge of English language.
Communication:
Interested candidates are invited to send:
- their full CV
- a motivation letter
to Prof. Michalis Vazirgiannis (michalis.vazirgiannis@gmail.com)
