Senior Data Scientist, Monetary Policy

Why Data Science And Engineering

The Data Science & Engineering 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 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.

In Data Science & Engineering, you will build the macroeconomic models, simulation frameworks, and policy mechanics that scale Roblox’s virtual economy. By analyzing Robux currency dynamics, global pricing strategies, and developer exchange policies, your work will directly inform strategic decision-making, financial policy, and executive roadmaps on our road to connecting one billion users.

You will: 

• Develop, build, and refine macroeconomic models to forecast and monitor Robux money supply, velocity, inflation/deflation dynamics, and overall virtual economy health.
• Model and inform comprehensive currency exchange policies, encompassing fiat-to-Robux purchase pricing, regional purchasing power (PPP) adjustments, and Developer Exchange (DevEx) rates, to balance global user participation, developer incentives, and long-term platform sustainability.
• Design and run counterfactual simulations (e.g. causal inference frameworks, agent-based modeling) to evaluate the impact of proposed monetary policies, sink/faucet adjustments, and marketplace fee changes before execution.
• Analyze sink and faucet dynamics across the platform to balance liquidity, optimize developer economy mechanics, and prevent systemic economic imbalances.
• Partner closely with Product and Finance leadership to translate complex economic data into actionable policy recommendations and sustainable growth strategies.
• Establish robust economic indicators and monitoring systems to track real-time macro-health metrics, liquidity risks, and structural shifts in user behavior.
• Communicate complex strategic findings and macroeconomic trade-offs to non-technical stakeholders to directly influence company-level roadmaps and economic policy decisions.
• Promote technical excellence in quantitative policy analysis, econometrics, and simulation methodologies across the broader Data Science and Engineering team.

You have: 

• 5+ years of industry or research experience applying quantitative economic modeling, econometrics, or simulation frameworks to analyze policy, marketplace dynamics, or user behavior.
• Deep expertise in quantitative methodologies including time series forecasting (e.g., VAR, state-space models), causal inference (e.g., synthetic control, diff-in-diff), structural macro modeling (e.g., DSGE), and counterfactual simulation techniques (e.g., agent-based modeling).
• Proven track record working with large-scale transactional or platform data to analyze micro-level user behaviors and aggregate them into macro-level economic insights.
• Demonstrated ability to lead project areas from scratch, translating ambiguous business and policy questions into rigorous quantitative frameworks and iterative research deliverables.
• Strong communication skills to explain complex economic trade-offs, risk scenarios, and simulation results to non-technical stakeholders in Finance and Product leadership.
• An Advanced Degree (MSc or PhD) in Economics, Econometrics, Quantitative Finance, Statistics, Operations Research, Physics, or a related quantitative field.

You are:

• A systems thinker.
• Curious and truth seeking.
• A deep collaborator. You understand where your skills provide differential value and complement others, and how the strengths of others complement you.
• Driven by strategic impact. You are passionate about informing high-stakes company decisions in complex, fast-moving environments.