Description
- Analyzing and optimizing real-time bidding strategies and online auction mechanics;
- Developing new or improving existing models of event predictions;
- New feature engineering for multiple machine learning models:
- User embeddings and clustering; fraud detection, etc.
- Cross-device user identification, cookieless mechanisms development;
- Mining different data sources;
- Supporting existing codebase for data integration and production support for our core models.
- Advanced knowledge of Python using standard DS packages (numpy/pandas/scikit, etc.); Being able to optimize and speed-up code.
- 3+ years of RTB Auction or similar online technologies.
- Algorithms and Data Structures (e.g., sorting, search tree, binary heap, trie; time & mem complexities of algorithms)
- Probability and Statistics (e.g., hypothesis testing; Markov process and its stationary distributions, stochastic matrix and its properties; Bayesian inference)
- ML & DS (e.g., dimensionality reduction, geometry of PCA / SVD and of L1 / L2 regularisation, Decision trees and their ensembles, collaborative filtering, Thompson sampling / MCMC, Neural Networks, etc.)
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