Staff Data Scientist – Consumer Product at Twitter

  • Remote Data Science Jobs
  • Part time
  • 5 months ago
  • USA
  • Shift Day
  • Job Qualifications Bachelor
  • Number of vacancies 1 opening
  • Job level Executive

Job Description

Staff Data Scientist

  • Consumer Product – Health Team
  • Remote, USA

By applying for this role, you could choose to work in the following locations:

  • US – Remote US
  • San Francisco

What You’ll Do at Twitter

  • Defending the health and integrity of the public conversation is Twitter’s top priority.
  • The Health Data Science Team partners with Product, Engineering, and Policy to rigorously understand and quantify Twitter’s highly complex and adversarial Health space and use this understanding to empower the Health Organization to better protect our users.
  • As a Staff Data Scientist on the Health Data Science Team you will:
  • Leverage data to identify unwanted interactions, violations of Twitter’s policies, misinformation, and other platform abuse then mitigate those issues with models or quantitatively driven product changes.
  • Design, implement, and analyze experiments to determine how new models or products improve the health of the platform.
  • Conduct analyses to better understand the determinants of the health and integrity on Twitter. Use this understanding to suggest product improvements.
  • Create accurate and statistically sound summary metrics to evaluate the performance of Health related products and motivate teams’ targets/KRs.
  • Communicate findings to executives and cross-functional teams.
  • Review other data scientists’ code and results to foster a culture of rigorous analysis and constructive feedback.
  • Help set the team direction by driving cross-functional alignment on projects and priorities.

What it takes

  • Advanced degree in a discipline that uses statistical analysis or mathematical modeling and 4+ years of work experience (or 7+ years of total work experience).
  • Experience measuring and mitigating consumer products’ vulnerability to manipulation and subversion.
  • Experience with one or more of the following in an applied business setting: experimental design and analysis, quasi-experimental analysis, and machine learning.
  • Track record for executing projects and leading complex, multi-functional projects with several dependencies, including Legal and Policy teams.
  • Strong proficiency with Python / R and SQL; familiarity with Spark.
  • Experience mentoring junior data scientists.
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