The Sales Intelligence team at Twitter works with our global sales and product teams to develop analytical insights for Twitter's advertising products, marrying product usage data with market trends (past, present, and future).
As a data scientist on the Sales Intelligence team, you are a technical innovator, capable of driving deep insights based on large quantities of data as well as building tools that support the Sales team’s efforts. You are highly analytical and detailed-oriented, but capable of thinking independently, and your hunger for working with data is only matched by your hunger for working at Twitter.
Success in this role means
Leading significant or long-term projects contributing to the overall growth and profitability of Twitter.
A highly proactive and independent spirit in which you are able to drive your initiatives with minimal guidance and input.
Presenting strategic insights and recommendations, to senior management and stakeholders in the Sales, Finance, Revenue, Marketing, and Support organizations critical to maintaining or developing long-term relationships with key brands.
Developing innovative, long-term strategies used to promote Twitter's advertising products.
Conducting complex statistical analysis of data related to sales, revenue, advertisers, as well as the trends and behavior that involve them.
Developing tools that enables the Sales Intelligence team execute against their own, varied projects.
Researches and selects from a variety of different available data sources to obtain sales, revenue, product, and market trends.
Independently performs complex statistical analysis to evaluate current and potential marketing strategies and long-term business goals.
Creates new analytical tools for effective analysis of product-related data.
Develops analytical models that help sales drive insight around topics such as risk, yield, and ROI.
Conducts experiments to determine optimal product usage to help drive analytical insights into best practices initiatives.
Trains, directs and supervises teams of junior analysts.
Extensive experience using quantitative analysis techniques (e.g., statistics, regression, and pattern recognition) as well as qualitative analysis techniques (e.g. case studies, content) to solve problems.
Extensive experience researching and manipulating complex and large datasets using MapReduce architectures like Hadoop.
Advanced knowledge of complex analytical packages including, but not limited to, R, SPSS, Stata, and SAS.
Advanced knowledge of SQL or any other form of database querying language.
Advanced knowledge of data visualization principles. Bonus: Experience with visualization technologies like d3, Raphael, Processing.js and Polymaps.
Strong programming knowledge, specifically in data manipulation and analysis, using languages including, but not limited to, Ruby, Python, or Perl.
Experience in the digital marketing industry and familiarity with popular digital advertising platforms, CPC/E/M/A campaigns, and measuring ROI.
Bonus: Published insights in relevant topics.
Demonstrated team leadership or project management skills.
Excellent verbal and written communication.
MS/PhD in a quantitative field of study, such as statistics, applied mathematics, computer science or another related field.
3+ years of relevant experience in the internet or social media industries.
Twitter - 11 months ago
Here's less than 140 characters for ya: trivial texts or not, every one's all a-twitter about tweeting. Twitter operates a free...