Quantitative Researcher/Statistician (Revenue Optimization)
Yelp, San Francisco, CA
Connecting people with great local businesses
What You Will Do:
- Conduct end-to-end analyses, from wrangling data via SQL or Python, to statistical modeling, to hypothesizing and presenting business ideas.
- Work with large, complex datasets.
- Lead the development of predictive and causal models around tasks such as customer acquisition, customer retention, and ad traffic forecasting.
- Productionize and automate models within Python services.
We Are Looking For:
- Experience with statistical software and packages (pandas/statsmodels/sklearn within Python, R, etc).
- Experience with statistical modeling for the purposes of predictive accuracy, forecasting, or causal inference.
- A love for writing beautiful code. You don’t need to be an expert, but experience is a plus and we will expect you to learn on the job.
- The curiosity to uncover promising solutions to new problems and the persistence to carry your ideas through to an end goal.
- Comfort in using a Unix environment.
- Minimum MS in statistics, econometrics, applied math, biostats, or other quantitative disciplines.
- A PhD in statistics, econometrics, applied math, biostats, or other quantitative disciplines.
- SQL programming experience.
- Experience with MapReduce or Spark.
Yelp connects people with great local businesses. Our users have contributed approximately 127 million cumulative reviews of almost every type of local business, from restaurants, boutiques and salons to dentists, mechanics, plumbers and more. These reviews are written by people using Yelp to share their everyday local business experiences, giving voice to consumers and bringing “word of mouth” online.
Want to learn more about Yelp? Visit Yelp's website.
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