64 day(s) ago

Staff Data Scientist

Negotiable Salary


United States
English: Advanced, Native Speaker
Experience: 3+ years
Employment: Full-time

Twitter

San Francisco
Company size: Large company (more than 300 employees)
Twitter is what’s happening in the world and what people are talking about right now.

Responsibilities

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.

Requirements

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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