Core Experience (CoreX) is focused on making TripAdvisor a habit for our travelers. Helping the people who come to TripAdvisor find and become part of a community of travelers with similar interests is a key Mission for us.

CoreX is hiring a Data Scientist to development relevant audiences and optimize ad devliery to hit our advertisers’ KPIs. This role will mine our 700m+ reviews, photos, and videos, 1m+ locations, and 450m+ monthly unique visitors to build on our first party data advantage. The developed models and data strategies will maximizing our adversting business and drive contextual, relevant ads to our consumers.

This is a great opportunity to make the world’s largest travel site even better, while enjoying the energy and rapid pace of a startup. This role requires very strong emphasis on data analysis and advanced analytics.

Key areas of responsibility:

• Apply machine learning and statistical methods to solve large scale problems, including: product monetization and audience segmentation

• Perform data analysis to support key decision making to evaluate opportunities for revenue optimization

• Oversee full life-cycle of analytical model development to optimize audience monetization

• Develop predictive models for user engagement and buying behavior

• Identify opportunities for revenue growth via user segmentation and personalized content

• Mentor junior team members

• Partner with Product Management and Engineering to create product requirements and specification documents for new features and products

What We Seek:

• 2+ years of experience in eCommerce, recommender systems, user choice models, classification, online auctions, A/B testing, digital advertising, or marketing analytics
• A results-oriented person who thrives on data and measurements.

• Ability to derive practical solutions to business problems from not-always-perfect data of formidable size

• Proven track record of translating business needs into data-driven solutions.

• Demonstrated ability of communicating complex analytical issues to technical and business audiences

• Proficiency in data transformation, cleansing and interpretation

• Expert SQL skills, experience with Big Data stack (Hadoop/Hive/Pig/Spark/etc.) and proficiency with statistical programming environment (e.g. R, Python)

• Masters/Ph.D. in quantitative field

• Experience managing or mentoring junior team members

• Ability to work well with colleagues across multiple global office.

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