WHY DATA SCIENCE & ANALYTICS?

The Data Science & Analytics organization's 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 toolbelt 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 creators.

WHY CREATOR PLATFORM?

At Roblox, the Creator Platform team is responsible for the systems that determine how creators build, publish, earn, and thrive on the platform. As a Senior Data Scientist, you will be the primary strategic data partner across some of the most business-critical and safety-sensitive areas in the creator ecosystem — including creator reputation, publish gating, anti-abuse, rewards, data foundations, and AI enablement.

This is a high-ownership, high-autonomy role. You will work across trust & safety, measurement, data infrastructure, and AI-enabled analytics — owning end-to-end problem framing, model development, and executive-facing recommendations in areas that directly shape platform integrity and creator success.

You Will:

• Own Creator Reputation & Publish Gating: Serve as the primary DS owner for the Creator Reputation Model and Good Standing score — ML systems that estimate creator trustworthiness and gate publishing access for new or alt accounts before they accumulate creator history. Maintain and improve the auto-approval model for DevEx requests.
• Build & Maintain Anti-Abuse Models: Lead anti-abuse modeling for creator rewards and creator analytics, ensuring the integrity of creator incentive systems and identifying bad actors at scale.
• Drive Creator Data Foundations: Serve as DRI for core creator data infrastructure — documenting all key creator tables, designing trustworthy data contracts, and building the semantic layers and analytical frameworks that enable reliable self-serve analysis across the team.
• Enable Agentic & AI-Powered Analytics: Lead DS AI enablement for the creator org — building skills, evaluation frameworks, and scalable AI-enabled workflows that reduce analyst toil and elevate the team's analytical capacity.
• Own Creator Analytics Reporting: Define top-line success metrics and own measurement for creator analytics, providing leadership with a clear, consistent view of creator health and platform performance.
• Support Creator Store & Select: Provide coverage for Creator Store safety scores, store metrics, and asset usage analysis. Serve as a dedicated DS partner for Select, helping shape how we open access to early-stage creators as creator reputation becomes a core input to eligibility.
• Create Zero-to-One Frameworks: Define analytical standards and measurement approaches for new, ambiguous product areas — translating complex technical systems into interpretable, movable metrics for product and engineering leadership.

You Have:

• Seniority & Breadth: High Senior or Principal-level DS experience, with a track record of owning complex, cross-functional data problems end-to-end — from problem framing and data infrastructure through modeling, experimentation, and executive communication.
• ML & Trust/Safety Chops: Proven ability to build, evaluate, and maintain ML models, especially for trust & safety, anti-abuse, or reputation systems. Experience with ecosystem or marketplace settings is a strong plus.
• Experimentation & Causal Inference: Strong statistical rigor, experimentation design, and causal inference skills — ideally applied in complex, mediated settings where simple A/B tests don't tell the full story.
• Data Foundation Expertise: Ability to contribute to the data foundation layer for AI — including table documentation, semantic layer design, data contracts, and trustworthy infrastructure for AI-enabled analysis.
• AI for Analytics: Deep understanding of agentic and self-serve analytics use cases, including how to turn DS workflows into scalable, AI-enabled products. Familiarity with evaluation frameworks for AI outputs.
• Technical Depth: Expert-level SQL and Python, with enough engineering fluency to work effectively across data pipelines, model outputs, and production-facing systems.
• Communication & Influence: Excellent written and verbal communication skills; able to translate technical findings into clear product and business recommendations for senior stakeholders.
• Comfort with Ambiguity: Experience operating independently in zero-to-one environments — defining the problem, building the data, and owning the answer without a playbook.
• Technical Leadership: Ideally, someone who can raise the bar for adjacent DS workstreams through mentorship, code review, and cross-functional partnership.
• Academic Background: BS, MSc, or PhD in Computer Science, Statistics, Applied Math, or a related quantitative field.