Economist - Advertising Finance

Job ID: 1383865 | Services LLC


Sponsored Advertising Finance at is seeking an exceptional Economist to join us. The most important question the team trying to answer includes: What are the long-term impacts of our initiatives? Where will Advertising’s growth come from in the next year? How big the Advertising business become over the next three years? Which widgets are poised to quintuple in size? What are the interactions between consumer and Ads business?
We’re building a team to answer these questions using economics methods. This Economist role will collaborate directly with other economists, data scientists, financial managers and engineers to do causal impact analysis, build accurate predictive models, and will have exposure to senior leadership as we communicate results and provide scientific guidance to the business.
A successful candidate will be a problem solver who excels in translating broad business problems into specific analytics projects, enjoys diving into data, is excited by difficult modeling challenges, and possesses strong communication skills to effectively interact with the business teams.

Key Responsibilities
· Collaborate with economists, data scientists, financial managers, and business leaders to define product requirements, provide science support, and communicate feedback.
· Implement economics methods to solve specific business problems utilizing code (Python, R, Scala, etc.).
· Improve existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters.
· Presenting data in a format that is immediately useful to answer the critical business questions.


· PhD in Economics or a related field
· Outstanding causal inference modeling and economics analysis skills.
· Proficiency in at least one statistical software package such as Python, R, Matlab, or Stata.
· Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to scientists, engineering teams and business audiences.


· Experience with machine learning applications, and applied time series forecasting.
· Experience working with very large, disparate data sets and big data tools such as Spark.
· Proficiency in one or more production languages (Python, Scala, Java, C++)


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