Data Scientist, Analytics
Company Name:-
Facebook
Job Location:-
Menlo Park, CA 94025
Job Summary:-
Were looking for Data Scientists to work on our core and business products (ex.
Instagram, Messaging, Growth, Engagement, Ads) to help shape the future of what we build at Facebook.
You will enjoy working with one of the richest data sets in the world, cutting edge technology, and the ability to see your insights turned into real products on a regular basis.
The perfect candidate will have a background in a quantitative or technical field, will have experience working with large data sets, and will have some experience in data-driven decision making.
You are focused on results, a self-starter, and have demonstrated success in using analytics to drive the understanding, growth, and success of a product.
Apply your expertise in quantitative analysis, data mining, and the presentation of data to see beyond the numbers and understand how our users interact with both our consumer and business products
Partner with Product and Engineering teams to solve problems and identify trends and opportunities
Inform, influence, support, and execute our product decisions and product launches
The Data Scientist Analytics role has work across the following four areas:
Product Operations: forecasting and setting product team goals, designing and evaluating experiments, monitoring key product metrics, understanding root causes of changes in metrics, building and analyzing dashboards and reports, building key data sets to empower operational and exploratory analysis, and evaluating and defining metrics
Exploratory Analysis: proposing what to build in the next roadmap, understanding ecosystems, user behaviors, and long-term trends, identifying new levers to help move key metric, and building models of user behaviors for analysis or to power production systems
Product Leadership: influencing product teams through presentation of data-based recommendations, communicating state of business, experiment results, etc.
to product teams and spreading best practices to analytics and product teams
Data Infrastructure: working in Hadoop and Hive primarily, sometimes MySQL, Oracle, and Vertica, and automating analyses and authoring pipelines via SQL and Python based ETL framework
Bachelors/Masters plus experience doing quantitative analysis wit
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