CRITEO is looking to recruit top-notch researchers for its headquarters in Paris, France.
Your mission: - Click prediction: How do you accurately predict if the user will click on an ad in less than a millisecond? Thankfully, you have billions of datapoints to help you. - Recommender systems: A standard SVD works well. But what happens when you have to choose the top products amongst hundreds of thousands for every user, 2 billion times per day, in less than 50ms? - Auction theory: In a second-price auction, the theoretical optimal is to bid the expected value. But what happens when you run 15 billion auctions per day against the same competitors? - Explore/exploit: It's easy, UCB and Thomson sampling have low regret. But what happens when new products come and go and when each ad displayed changes the reward of each arm? - Offline testing: You can always compute the classification error on model predicting the probability of a click. But is this really related to the online performance of a new model? - Optimisation: Stochastic gradient descent is great when you have lots of data. But what do you do when all data are not equal and you must distribute the learning over several hundred nodes? Are you interested in tackling such problems in an environment where your algorithms are deployed by a team that sits next to you? To qualify for this mission, you need: - PhD in Statistics, Machine Learning or a related field, with a previous major in Computer Science. - Coding experience in Python, C# or Java. - Great oral and written communication and presentation skills. - A track record and interest in contributing to publications, presentations, external collaborations and service to the research community. Preferred Skills: - Experience in the optimization of online advertising - Experience working directly with Hadoop data platforms. We have the challenges, we have the data, we need you. Are you up to the challenge? If you think so, contact Nicolas Le Roux at n.ler...@criteo.com . _______________________________________________ uai mailing list uai@ENGR.ORST.EDU https://secure.engr.oregonstate.edu/mailman/listinfo/uai
