WHY DATA SCIENCE & ANALYTICS
The Data Science & Analytics organizations mission is to increase our speed frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering product analytics experimentation causal inference statistical modeling and machine learning. Aligned and partnering with product verticals we use this extensive tool belt to discover new opportunities and unmet use cases influence and shape the product roadmap and prioritization build data products and measure impact on our community of players and developers.
WHY CONTENT SAFETY
Content safety and moderation are paramount to maintaining a positive engaging and trustworthy platform experience for our global this role you will apply your expertise in data science statistics and causal inference to strategically define measure and improve the detection and mitigation of harmful user-generated content and violative on-platform behaviors. Your focus will be on asset-based content across the platform - including games avatars and emerging in-game behaviors - by establishing reliable ground truth datasets and developing robust prevalence measurement methodologies. You will collaborate closely with Product Engineering Legal Policy and Compliance teams acting as the quantitative expert who guides our defensive strategy against evolving safety threats and ensures accountability and scalable solutions. This is a critical opportunity to build innovative detection systems define what we measure and prove the impact of our safety efforts.
You Will:
- Establish and monitor robust prevalence measurement methodologies to accurately quantify the overall level of harmful content and behavior on the platform providing the authoritative source of truth for organizational safety goals.
- Develop and validate comprehensive ground truth datasets for harmful UGC and violative on-platform behaviors ensuring high quality and alignment with the latest platform policies.
- Deepen our understanding of violations by conducting exploratory analysis on current and emerging threat landscapes providing data-backed recommendations on where Product and Engineering should strategically invest detection and moderation resources.
- Design implement and analyze sophisticated experiments for new moderation and safety enforcement features communicating results to our primary partners in Product and Engineering to guide development while also collaborating closely with Policy Compliance and Legal teams for full strategic alignment.
- Leverage advanced causal inference methodologies to accurately measure the effectiveness and potential systemic impacts of various safety initiatives on player experience and platform integrity.
- Communicate strategic insights and present recommendations to leadership and all cross-functional partners translating complex statistical findings on prevalence ground truth quality and effectiveness into actionable strategies for Product Engineering Policy Compliance and Legal.
- Partner with ML and Data Engineering teams to ensure model development reporting and detection systems are built on statistically sound ground truth and measurement frameworks.
You Have:
- 10 years of industry experience in data science economics analytics or machine learning engineering
- 7 years of experience using scripting languages (Python R) and big data query/processing languages and tools such as SQL Hive Spark and Airflow
- Knowledge of ML and Deep Learning either via formal training or industry experience
- Ability to apply creative first-principles reasoning to solve ambiguous problems
- Experience developing large-scale safety or moderation systems as well as experience with content platforms specifically user-generated content
- Advanced Degree and/or PhD in Statistics Computer Science Physics Applied Math Economics or other related quantitative fields
Required Experience:
Staff IC
WHY DATA SCIENCE & ANALYTICSThe Data Science & Analytics organizations mission is to increase our speed frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering pro...
WHY DATA SCIENCE & ANALYTICS
The Data Science & Analytics organizations mission is to increase our speed frequency and acumen of making decisions at scale by instilling a data-influenced approach to building products. We cover a wide area of the data spectrum including analytical data engineering product analytics experimentation causal inference statistical modeling and machine learning. Aligned and partnering with product verticals we use this extensive tool belt to discover new opportunities and unmet use cases influence and shape the product roadmap and prioritization build data products and measure impact on our community of players and developers.
WHY CONTENT SAFETY
Content safety and moderation are paramount to maintaining a positive engaging and trustworthy platform experience for our global this role you will apply your expertise in data science statistics and causal inference to strategically define measure and improve the detection and mitigation of harmful user-generated content and violative on-platform behaviors. Your focus will be on asset-based content across the platform - including games avatars and emerging in-game behaviors - by establishing reliable ground truth datasets and developing robust prevalence measurement methodologies. You will collaborate closely with Product Engineering Legal Policy and Compliance teams acting as the quantitative expert who guides our defensive strategy against evolving safety threats and ensures accountability and scalable solutions. This is a critical opportunity to build innovative detection systems define what we measure and prove the impact of our safety efforts.
You Will:
- Establish and monitor robust prevalence measurement methodologies to accurately quantify the overall level of harmful content and behavior on the platform providing the authoritative source of truth for organizational safety goals.
- Develop and validate comprehensive ground truth datasets for harmful UGC and violative on-platform behaviors ensuring high quality and alignment with the latest platform policies.
- Deepen our understanding of violations by conducting exploratory analysis on current and emerging threat landscapes providing data-backed recommendations on where Product and Engineering should strategically invest detection and moderation resources.
- Design implement and analyze sophisticated experiments for new moderation and safety enforcement features communicating results to our primary partners in Product and Engineering to guide development while also collaborating closely with Policy Compliance and Legal teams for full strategic alignment.
- Leverage advanced causal inference methodologies to accurately measure the effectiveness and potential systemic impacts of various safety initiatives on player experience and platform integrity.
- Communicate strategic insights and present recommendations to leadership and all cross-functional partners translating complex statistical findings on prevalence ground truth quality and effectiveness into actionable strategies for Product Engineering Policy Compliance and Legal.
- Partner with ML and Data Engineering teams to ensure model development reporting and detection systems are built on statistically sound ground truth and measurement frameworks.
You Have:
- 10 years of industry experience in data science economics analytics or machine learning engineering
- 7 years of experience using scripting languages (Python R) and big data query/processing languages and tools such as SQL Hive Spark and Airflow
- Knowledge of ML and Deep Learning either via formal training or industry experience
- Ability to apply creative first-principles reasoning to solve ambiguous problems
- Experience developing large-scale safety or moderation systems as well as experience with content platforms specifically user-generated content
- Advanced Degree and/or PhD in Statistics Computer Science Physics Applied Math Economics or other related quantitative fields
Required Experience:
Staff IC
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