Data Scientist
As a Twitter Data Scientist, you will be designing, building, and shipping complex models that learn from Twitter data. We are looking for folks that are passionate about understanding data, are well versed in scalable data mining and machine learning techniques, and love to build models. If challenges like the Netflix prize and KDD cup excite you, this is your dream job. A passion for measuring model quality and iteratively improving them using feature engineering is a big plus.
Responsibilities
- Apply data-mining, machine learning and/or graph analysis techniques for a variety of modeling and relevance problems involving users, their relationships, their tweets and their interests
- Build complex statistical models that learn from and scale to petabytes of data
Use Map-Reduce frameworks such as Pig and Scalding, statistical software such as R, and scripting languages like Python and Ruby
Write and interpret complex SQL queries for standard as well as ad hoc data mining purposes
Define metrics, understand A/B testing and statistical measurement of model quality
Understand and leverage crowdsourcing and human computation approaches to data labeling
Requirements
MS or PhD in computer science, data mining, machine learning, statistics, math, engineering, operations Research, or other quantitative discipline
Fluent in one or more object oriented languages like Java, Scala, C#, C++
- Experience with scripting languages like Python or Ruby, etc
Experience with feature engineering and model building
Experience with statistical programming environments like R or Matlab
Experience in mapping business needs to engineering systems
Desired
Three or more years of industry experience
Experience with large datasets and map-reduce architectures like Hadoop and open source data mining and machine learning projects
- Active Twitter user
San Francisco, CA 94103
Full Time