Applied Scientist

• Experience developing quantitative models to support real-world decision-making under uncertainty
• Strong coding skills in Python, with the ability to move beyond prototyping and implement production-quality scientific code
• Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization
• Comfort working with messy, high-dimensional real-world data and translating ambiguous business problems into rigorous modeling approaches
• Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly

Nice to Have

• Experience in pricing, marketplace modeling, revenue management, supply/demand systems, inventory optimization, or risk modeling
• Background in real estate, housing, finance, or adjacent marketplace domains
• Familiarity with distributed data processing tools such as Pyspark
• Experience with machine learning methods broadly, including where deep learning can complement structured statistical modeling
• Experience working with large language models (LLMs) or vision-language models (VLMs)