— 2+ years of experience in data engineering or data science
— 2+ years of experience in Python 3
— Knowledge of common DS technologies such as Pandas, Scikit Learn, Keras, Tensor Flow, Numpy
— Hands-on experience with Apache Spark
— Experience of creating data lakes
— Experience of creating data processing pipelines
— English (Upper-intermediate+)
— Experience in ad tech or martech companies
— Understanding of ad tech ecosystem (RTB, DSP, SSP)
— Understanding of ad performance data (metrics, features, optimization approaches)
— Koalas
— ML Flow
— Deltalake
— Participation in the development of a global data science product;
— The opportunity to take a leading position in a growing team;
— Interesting tasks and a team of experienced colleagues in our team;
— Experience in an international company with offices in New York, Paris, Tel Aviv, and Kyiv.
— Setup and maintain the infrastructure for R&D needs
— Support DS team with preprocessing pipelines
— Create the architecture and set up a data lake
— Create a workflow for continuous deployment of ML models
— Work on the performance optimization of existing DS related functions
— Take part in solving problems of bid and creative optimization, conversion rate prediction, outlier detection, time-series prediction
We are a fast-growing social ad tech company. Vetted by Facebook, Twitter, Instagram and Snapchat as an Official Partner, we empower brands and advertisers to outperform their social ads campaigns on social networks at scale.
Preferred tool of 4000+ companies worldwide, our cutting-edge platform is used everyday by advertisers (Meetic, L’Occitane, Cheerz, Sarenza, Hawkers...) and agencies (Havas, Dentsu-Aegis, GroupM...) to automate and optimize all their social ads campaigns in one place.
We’re changing the way people run ads on social media and we participate in creating the future of interaction between brands and people.
Today, we’re looking for passionate people, who like taking initiative, solving problems and who can thrive in a fast and growing environment.