Senior Data Scientist - Safety & Security
New
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Wikimedia FoundationOnline safety
Listing locations: USA; Location base: USA. We are currently able to hire in the following US States and countries: Brazil, Canada, Colombia, Germany, Ghana, India, Indonesia, Italy, Kenya, Mexico, Morocco, Netherlands, Poland, Singapore, South Africa, Spain, Switzerland and the United Kingdom., Availability for critical meetings and synchronous collaboration between 13:00 and 19:00 UTC.Full-TimeSenior
Salary109,563 - 173,129 USD per year
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Job Details
- Required Skills
- PythonSQLMachine LearningSparkR
Requirements
- Experience with experimental design and statistics or machine learning methods.
- Experience using AI coding assistants for data analysis and other technical tasks.
- Fluency in R or Python and common version control and command-line-based tools.
- Fluency in SQL and experience working with large-scale data.
- Experience collaborating with product development teams to test, analyze, and evaluate user-facing features for an online platform.
- Ability to explain data and insights clearly to non-specialist audiences.
- Use discretion and competence when handling sensitive or confidential data.
- Prior experience in trust and safety, information security and privacy, or fraud and anti-abuse is a plus.
- Exposure to ethical data management and privacy practices is a plus.
- Experience with Superset, Growthbook, or other open-source testing, data visualization, or reporting tools is a plus.
Responsibilities
- Partner with product managers, engineers, designers, and other product development colleagues.
- Recommend product direction and data strategy, surface insights, and interpret results.
- Deliver quantitative data and insights to inform strategy, product decisions, and assessments of product development work.
- Communicate results and data-backed recommendations to stakeholders across functions.
- Build measurement strategies and evaluate experiments using Bayesian and Frequentist approaches.
- Develop queries and code to work with large-scale internal and external data repositories.
- Build automated, self-service dashboards to track product success and health metrics.
- Help product teams instrument features, perform data quality assurance, and use A/B testing tools.
- Collaborate with research scientists and security engineers to develop and evaluate AI models for malicious user-authored code.
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