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 groups, we use this vast tool belt to discover new opportunities and unmet use cases, influence and shape the product roadmap and prioritization, build data products and measure the impact on our community of players and developers.

Roblox is used by tens of millions of people every day, across almost all devices (mobile, desktop, console, VR, etc.). Our users expect top-notch app performance: lightning-quick launches, buttery smooth animations, and rock-solid stability.  As a Data Scientist on the team, you will partner with engineers, product managers, and leaders across the company in our efforts to create the best app experience on any device for Roblox. This area is pivotal to our company’s success, directly impacting all users and being one of Roblox's highest priorities. You will define KPIs and measure the impact of key performance improvements while leveraging statistics, analytics, and experiments to influence decisions and strategies related to enhancing the performance and reliability of the Roblox app. 

You Will:

• Define and measure success metrics for App performance. Determine which performance metrics matter to end users and how app performance impacts user engagement and monetization.
• Establish an understanding of the trade-offs between different performance levers and use these insights to influence strategies, ensuring right-sized investments that optimize business growth and user experience.
• Access raw data, transform it, analyze it, and present it in a compelling and understandable way. Perform deep dives to uncover new insights and opportunities.
• Operationalize and scale metrics monitoring by building tools that enable quick slicing and dicing of data as well as root cause analysis. Collaborate with engineers to detect and investigate abnormal trends, identifying opportunities for improvement.
• Use A/B experiments and causal inference methods to evaluate the success of feature launches.
• Navigate ambiguity and work with stakeholders across various organizations, including User, Growth, Engine, and Creator teams.

You Have:

• An advanced degree or equivalent experience in Statistics, Applied Math, Physics, Engineering, Computer Science, Economics, or a related quantitative field.
• 5+ years of industry experience in a data science role, preferably with a background in app and system performance.
• Strong experience working with large datasets and proficiency in SQL, R/Python, and data visualization tools.
• Deep knowledge and practical application of statistical methods, causal inference techniques, and experimental design.
• Ability to drive an area as an individual contributor and thought leader.
• Ability to apply creative, first-principles reasoning to solve ambiguous problems.
• Strong communication skills to present analytics results and data storytelling effectively, influencing engineering teams and leaders.

You Are:

• Passionate about data. You have the curiosity and self-drive to continuously learn new techniques and tools to extract value from data. 
• Highly self-driven. You thrive with freedom and autonomy and are excited by the ambiguity that comes from exploring a new problem space. 
• A strong communicator. You understand that analysis must be presented in meaningful ways and engage in spirited discussions about the findings. You can explain technical concepts to a non-technical audience.
• A capable statistician. You understand the value of characterizing data by its distribution. Covariance, Bias, and Conditional Probability are concepts that you rely on every day.
• An expert transforming data with SQL and a scripting language such as Python or R. You’re experienced in automating efforts and crunching massive volumes of data.
• Experienced in developing models to draw insights from data. You use regression, data mining, and other statistical techniques to create new, scalable solutions to solve challenging business problems. You understand when to apply the appropriate methodology to maximize impact pragmatically.