Data Scientist AdTech )

Requirements

Essential requirements

5+ years experience working as a Data Scientist or ML Engineer in industry (preferably in advertising) is a must, where you have gained hands-on experience delivering data science products,

Experience in taking data science projects from concept to production in an industry setting,

Fluent in statistical analysis, data mining, and machine learning,

Strong application and ML development experience in Python, functional as well as object oriented programming,

A postgraduate degree in a relevant quantitative field (e.g. applied mathematics, statistics, engineering, computer science, physics, operations research, economics, behavioral sciences) is a plus,

Proficient in SQL, PySpark, TensorFlow, Sklearn,

Experience in GCP or AWS

Experience with developing or supporting high performance APIs,

Enthusiasm for solving interesting problems,

Willingness to learn and work in a team-oriented and constantly changing environment.

Domain:

In this role your main focus would be on our Ad-Exchange Optimization projects

Bid Price Optimization - Optimize to improve the likelihood of winning auctions with supply-side partners,

Floor Price Optimization - Optimize to improve demand-side valuation of supply,

Supply Path Optimization - Optimize auctions to improve efficient utilization of finite bandwidth with demand-side partners,

Auction Models - Optimizing different auction setups - 1st price, 2nd price, Waterfall.

Research and Development

Our Machine Learning Engineer role includes the following responsibilities:

Designing, developing, and researching cutting edge Machine Learning systems, models, and schemes in many different areas of Adtech,

Developing real-time algorithms for campaign and bidding optimization,

Discovering insights/patterns in exchange data, and developing methods to leverage/extract/process/analyze complex, high volume, high-dimensional datasets,

Designing experiments, overseeing A/B testing, evaluating the quality of derived assets and developing dashboards to continuously monitor model performance,

Studying, transforming, and converting data science prototypes,

Searching and selecting appropriate data sets,

Performing statistical analysis and using results to improve models,

Training and retraining ML systems and models as needed,

Identifying differences in data distribution that could affect model performance in real-world situations.

Visualizing data for deeper insights,

Analyzing the use cases of ML algorithms and ranking them by their success probability,

Understanding when your findings can be applied to business decisions,

Reducing business problems into optimization problems,

Supporting, maintaining and enriching existing ML frameworks and libraries,

Verifying data quality and/or ensuring it via data cleaning.

What we offer

Working on data science products which play an integral role in the company, and which are widely understood and highly valued,

Unique opportunity to work on a wide variety of technically challenging and interesting data science projects, with hands-on exposure to a large number of current data science and engineering technologies and being able to solve complex productionising issues,

Chance to work with truly big data: we are currently processing 120 billion auctions a day and counting,

Join one of the top mobile advertising companies in the world, which is growing a phenomenal pace in terms of profits and market share,

Be part of a friendly, supportive and multicultural team.

Full time