About the job:
We are looking for outstanding machine learning research scientists whose skills span the entire spectrum of Machine Learning/Data-Science research, i.e. data-gathering/cleaning, modeling, implementation, publication and presentation. In particular we are seeking researchers with the following skills and experience to contribute to Criteo in driving the future of ad targeting, personalization, content extraction, content matching and other prediction problems.
- 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?
- Gather and analyze data, identify key prediction/classification problems, devise solutions and build prototypes
- Contribute to the exploration and creation of new scientific understanding
- Initiate and propose unique and promising modeling projects, develop new and innovative algorithms and technologies, pursuing patents where appropriate
- Stay current on published state-of-the-art algorithms and competing technologies
- Maintain world-class academic credentials through publications, presentations, external collaborations and service to the research community
- Develop high-performance algorithms for precision targeting, test and implement the algorithms in scalable, product-ready code
- Research and investigate academic and industrial data mining, machine learning and modeling techniques to apply to our specific business cases
- Interact with other teams to define interfaces and understand and resolve dependencies
- Oversee the creation of detailed technical documents, participate in academic conference, publish research papers
- Understand and mold the product direction by contributing innovative ideas, specifically as a result of data mining and experimental data modeling
- Experience in the optimization of online advertising
- Experience working directly with Hadoop data platforms.
- 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.