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The Ads Localization and International Expansion team owns and builds services and applications across Company WW Advertising focused on removing language barriers that prevent Advertisers from advertising globally across. Our mission is to enable millions of advertisers around the world to reach shoppers in their language of preference and accelerate their path to becoming global advertisers and brands. In addition, we are responsible for orchestrating the rollout of mission-critical software to enable the Advertising organization to expand its footprint internationally.
In this role, you will build solutions around our multi-channel and multi-lingual advertising offerings for our clients that connects technology, data, machine learning, human translators and marketing assets to deliver the best in class experience to our advertisers. You will use ideas from every facet of Data Science including Natural Language Processing, Speech to Text analysis, Machine Learning and artificial intelligence.
The charter of this team is to eliminate all barriers that prevent Company customers from advertising world wide. We are innovating in this space by building and rolling out new capabilities to allow advertisers to seamlessly launch campaigns across the globe in multiple markets. One of the key challenges that we are currently working on is to enable human independent translation workflow's for advertiser content, which is extremely difficult to automate through machine translations. The challenge is to rollout solutions which can be scaled without sacrificing the translation quality (critical to Advertiser content). We are also rolling out solutions for our clients to cover video translations and the ability to scale seamlessly between machine and human translations based on detailed analysis of Advertiser content.
You will LOVE this opportunity if you are:
Highly analytical: You solve problems backed with verifiable data. You focus on driving processes, tools, and statistical methods that support rational decision-making.
Technically fearless: You aren’t satisfied by performing ‘as expected’ and push the limits past conventional boundaries.
Team obsessed: You help grow your team members to achieve outstanding results. You foster a creative atmosphere to let scientists and engineers innovate, while holding them accountable for making smart decisions and delivering results.
Ambitious: You’re ambitious, yet humble. You recognize that there’s always opportunity for improvement - using introspection, feedback from teammates and peers to "raise the bar" for your team.
Engaged by ambiguity: You’re able to explore new problem spaces with unique constraints and non-obvious solutions.
M.S. or Ph.D. in Computer Science, Machine Learning, Statistics, Applied Mathematics, Information Retrieval, or related discipline
Breadth and depth knowledge in machine learning algorithms and best practices.
At least 5 years of hands-on experience in building Machine Learning solutions to solve real-world problems.
At least 3 years of experience with computer science fundamentals in object-oriented design, data structures, algorithm design, problem solving, and complexity analysis.
At least 3 years of experience with, at least, one modern programming language such as Java, Python, Scala, C++
Ph.D. Degree in quantitative field with a strong Machine Learning background
Experience in building large-scale machine-learning models for online recommendation, ads ranking, personalization, or search, etc.
Experience with Big Data technologies such as AWS, Hadoop, Spark, Pig, Hive, Lucene/SOLR or Storm/Samza
Strong proficiency with Java, Python, Scala or C++
Experience in computational advertising technology is a big plus
Published research work in academic conferences or industry circles.
Excellent oral and written communication skills, with the ability to communicate complex technical concepts and solutions to all levels of the organization
Company is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation
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