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X Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
San Jose, CA, USA; Mountain View, CA, USA.
Minimum qualifications: - Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 5 years work experience with a Master's degree).
- Experience with A/B testing methodologies.
Preferred qualifications: - Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
- Experience developing and using AI tools in the context of data science for large, consumer facing internet products.
About the jobAs a Data Scientist for Android and Business Communication (ABC), you will deliver critical insights, predictive models, and measurement frameworks to protect users across Rich Communication Services (RCS) and RCS Business Messaging (RBM) from spam, abuse, and malicious traffic.
In this role, you will analyze complex communication data to identify emerging abuse vectors, model adversarial behaviors, and guide product and engineering teams on anti-spam and trust and safety strategies. You will bridge technical excellence and product execution by designing end-to-end classification and detection pipelines, running robust offline and online evaluations, and translating complex investigative findings into actionable recommendations that safeguard ecosystem trust and enhance the messaging experience globally.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $163000 - $236000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Define and track core metrics for spam prevalence, false positives, enforcement efficacy, and user impact. Develop automated dashboards, anomaly detection alerts, and reporting pipelines to monitor ecosystem health in real time.
- Design and execute A/B tests and counterfactual analyses to evaluate the efficacy and side effects of anti-spam rules, ML model updates, and UI interventions.
- Partner closely with Product, Engineering, Policy, and UX teams to identify spam trends, prioritize enforcement roadmaps, and balance security with user engagement.
- Conduct exploratory data analyses on evolving adversarial behaviors in conversational messaging and present technical insights to cross-functional stakeholders.
- Evaluate and iterate on statistical models, heuristics, and classification algorithms (e.g., text classifiers, graph signals, behavioral anomaly detection) to detect spam, phishing, and unwanted traffic across P2P RCS and commercial RBM channels.
