Senior Data Scientist - Ecosystem and Learning Platform

WHY DATA SCIENCE & ANALYTICS?

The Data Science & Analytics organization's mission is to increase our speed, frequency, and acumen in 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 partnered with product verticals, we use this extensive tool belt to discover new opportunities and unmet use cases, influence and craft the product roadmap, and prioritize, build data products, and measure impact on our community of players and developers.

WHY ECOSYSTEM AND LEARNING PLATFORM?

The mission of the Ecosystem and Learning Platform Data Science team is to empower vertical data science teams and drive data-informed decision-making at scale. We do so by collaborating with vertical data science and cross-functional partners to solve complex business problems that span multiple areas of the Roblox ecosystem, develop scalable data science solutions and tools, and advance data science methodologies. 

Central to our mission are platformized tools that provide comprehensive solutions for company-wide experimentation, forecasting and anomaly detection needs, integrate diverse data sources, and offer scalable, accessible data science products that yield actionable insights for product areas across Roblox. As a member of this team, you will collaborate with product data science partners to develop and support core data science and machine learning models, and build platform solutions that streamline the model development and deployment process. 

You will also collaborate with product data science and cross-functional partners to bring structure and innovative solutions to complex business problems. In the process, you will help build cutting-edge methodologies and tools that advance data science within our company and set industry standards. If you are a self-starter who is curious and passionate about leveraging big data to create tangible business value and thrive in a dynamic, collaborative, and innovative environment, this is the place for you.

You Will:

• Develop and support core data science models and production pipelines used across the business.  
• Support the development and operations of a centralized platform for time series forecasting and anomaly detection.   
• Collaborate with data science and product partners to develop innovative and scalable solutions to measure ecosystem health, forecast business performance, and identify and quantify complex cause-and-effect relationships within the Roblox ecosystem. 
• Promote and uphold a high bar of technical excellence and enable the adoption of technical advances in data science. 
• Work closely with engineering and product partners to build scalable data science systems and tools. 
• Own the implementation and maintenance of DS self-serve tools and proactively identify opportunities to scale experimentation, causal modeling, and analytics insights through tooling and methodology. 
• Communicate effectively with technical and non-technical stakeholders to solve problems and influence decisions. 
• Cultivate strong partnerships with vertical data science teams, engineering, and product partners.

You Have:

• An Advanced Degree (MSc or PhD) in Statistics, Economics, Operations Research, Computer Science, Applied Math, Physics, Engineering, or other quantitative fields or have equivalent practical experience.
• 4+ years in developing and applying statistical methods, causal inference techniques, experiment design and analysis, time series modeling, or machine learning. 
• 4+ years of experience building scalable ETL data pipelines and dashboards. 
• 4+ years of experience in data science, machine learning, data engineering, analytics engineering or related fields. 
• 4+ years of experience in one or more scripting languages, such as Python.
• Demonstrated ability to lead or build project areas from scratch.