Senior Data Scientist, Ads Integrity
New
R
RedditTrust & Safety
This role is completely remote friendly within the United States.Full-TimeSenior
Salary$190,800 — $267,100 USD
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Job Details
- Experience
- With an M.S., 4+ years of industry data science experience, or with a Ph.D., 2+ years of industry data science experience.
- Required Skills
- PythonSQLMachine LearningData scienceNLP
Requirements
- Relevant experience in Data Science, Applied Science, or a related quantitative role, preferably in ads fraud, financial fraud, Trust & Safety, or platform integrity.
- Ph.D. or M.S. degree in Statistics, Economics, Computer Science, Applied Mathematics, or another quantitative field.
- 4+ years of industry data science experience with an M.S., or 2+ years with a Ph.D.
- Demonstrated experience building or shaping production detection and automated enforcement pipelines.
- Strong command of fraud or abuse detection methods, including label design, precision and recall tradeoffs, and false-positive analysis.
- Experience partnering closely with Product and Engineering teams to translate prototypes into production systems.
- Experience applying AI and large language models (LLMs) to practical data science workflows.
- Deep understanding of complex behavioral networks or large-scale activity patterns.
- Fluency in statistical analysis, Python, and SQL.
- Ability to tackle ambiguously defined problems and move to scalable, reusable solutions.
- Strong technical leadership and communication skills to influence roadmaps and align stakeholders.
Responsibilities
- Lead the measurement and detection strategy for ads fraud by defining fraud taxonomies, labels, sampling plans, metrics, and evaluation frameworks.
- Analyze large, complex datasets and networks of behavior to uncover emerging fraud patterns and size their impact.
- Design and develop scalable ads fraud detection and enforcement pipelines in partnership with Engineering and Machine Learning.
- Own the full detection lifecycle including backtesting, threshold calibration, evaluation, validation, monitoring, and incident response.
- Build and maintain statistical, machine learning, and GenAI-enabled models or prototypes.
- Balance fraud loss, platform and advertiser risk, customer experience, and operational capacity when recommending enforcement strategies.
- Partner across Ads and Safety to shape strategy, strengthen data foundations, and ensure solutions meet governance standards.
- Translate complex analyses into actionable recommendations for stakeholders and mentor junior team members.
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