Data Scientist, Product
Who We Are:
Twitter users generate many terabytes of data every day; Twitter engineers run hundreds of experiments; Twitter data scientists create increasingly sophisticated models of users and content.
The Analytics team at Twitter is at the intersection of all this data and strives to make it actionable to all business units around Twitter. We spearhead complicated and important analyses and think of other ways to make extremely large scale data easy to use to guide exploration and decision-making.
As a Twitter Data Scientist, you will work to make user behavior visible and clear in order to enable great product decision-making. While the term Data Science has been used to encompass a variety of diverse skill sets and responsibilities across industries, the focus of this role at Twitter is on influencing product decisions using data and modeling.
What You’ll Do:
You will be a key member of the Analytics team and work will directly influence the exciting new product areas that Twitter is building. In every decision that you influence, you will see the product improve and be more valuable to Twitter users.
As such, you will:
- Conduct analysis to learn from Terabytes of data.
- Apply advanced statistical techniques to model user behavior, identify causal impact and attribution, build and benchmark key metrics.
- Write Map-Reduce jobs in Scalding/Spark, complex SQL queries, R and Python scripts.
- Use data visualization tools such as Tableau or Zeppelin.
- Communicate findings to executives and cross-functional product teams.
Who You Are:
- You're a very experienced person who owns important project areas from start to finish.
- You influence entire organizations with the work you do. That work includes defining an important roadmap of data science work and executing it (perhaps in collaborations with others).
- You are highly technical and hands on but you wear a product manager hat easily to make your projects successful.
- You are a great communicator, capable of building meaningful presentations and analyses that tell a “story” passionate about insights, not just data.
- Able to synthesize methodology and data into actionable business and/or product strategy, and communicate findings to relevant business partners: product, engineering, and management teams.
- 4+ years of work experience involving quantitative data analysis to solve problems.
- Masters Degree or PhD in Economics, Statistics, Physics, Chemistry, Engineering, Computer Science or a related field.
- Fluent in one or more object oriented languages like Java, Scala, C#, C++.
- You are experienced with statistical programming environments like R, Matlab, Python.
- Capable of collaborating and working closely with cross-functional business, engineering and research partners to identify gaps and structure problems.
- Experience with handling large datasets and map-reduce architectures like Hadoop, and open source data mining tools.
We are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.
San Francisco applicants: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Engineering Hiring Process
Once your application is received, a recruiter will reach out pending your qualifications are a match for the role.
If your background is a match, you may have 1-2 technical phone interviews or be given the chance to provide a work sample depending on the role.
If the phone interviews go well or your work sample is strong, the final step includes interviews with 5-6 people held onsite in our office.
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