The core machine learning team for Snapchat ads is looking for the first few data scientists to support and enable the continued improvement...
The core machine learning team for Snapchat ads is looking for the first few data scientists to support and enable the continued improvements in the quality of our machine learning models. In this role you will work closely with senior machine learning engineers and product managers. You will apply state of the art statistical modeling techniques to estimate various performance metrics, identify the opportunity areas for model improvements, develop rigorous offline and online evaluation frameworks, and build tools to improve our understanding of complex deep learning models.The core modeling team is responsible for machine learning models and algorithms that predict engagement of Snapchat users with sponsored ads. We directly impact the value advertisers get from Snapchat ad-auction platform by matching each user with relevant ads. We are one of the primary driving forces behind innovations in machine learning algorithms and software at Snap Inc.What you'll do:Build state of the art statistical models to estimate various performance metrics that are not directly observed.Develop rigours offline and online metrics for model evaluation.Collaborate with machine learning engineers, build tools to understand complex machine learning models and identify areas of improvements for the model.Collaborate with product managers, apply your expertise in quantitative analysis, and generate actionable insights.Understand patterns in data to identify key product trends and new product opportunities.Create and test hypotheses.Communicate your findings to cross-functional stakeholders and help make data-informed product decisions.Minimum qualifications:Pursuing a Bachelor's degree in math, statistics, computer science, economics, or other quantitative field.Strong statistical knowledgeFluency in SQL or similar big data querying languages.Fluency in Python.2+ years of experience in mobile ad technology, auctions and ads marketplace.Preferred qualifications:Advanced degree in math, statistics, computer science, economics, or other quantitative fieldExperience with causal inference techniques, experimental design, metric design, and/or A/B testing.Experience with machine learning predictive modeling.Ability to initiate and drive projects to completion with minimal guidanceAbility to communicate the results of analyses in a clear and effective manner to a senior audience
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