What You Will Do- Develop algorithms for optimizing prices at scale.
- Design pricing experiments and use data for model training and pricing decisions.
- Use data to understand product performance and to identify improvement opportunities.
- Present findings to senior management to advise on business decisions.
- Collaborate with multi-functional teams across fields such as product, engineering, operations, and marketing to drive system development end-to-end from ideation to productization.
Basic Qualifications- Ph.D., M.S. or Bachelor's degree in Statistics, Economics, Mathemathics, Computer Science, Machine Learning, Operations Research, or other quantitative fields.
- Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics.
- Experience with exploratory data analysis, statistical analysis and testing, causal inference or ML model development.
- Ability to use Python to work efficiently at scale with large data sets.
- Proficiency in languages and tools like SQL, R, and Spark.
Preferred Qualifications- 3-5 years of industry experience.
- Proven experience as an Applied Scientist, Machine Learning Engineer, Product Data Scientist, Research Scientist, Software Engineer, or equivalent.
- Experience in algorithm development and prototyping.
- Experience in solving an ambiguous business problem in a structured and principled way
- Strong communication skills, including through documentation and presentations.
- Experience working in a marketplace-related problem space, esp. pricing optimization
- Experience designing large-scale price experiments and using the data for pricing decisions.
- Experience designing model architectures for pricing algorithms.
For New York, NY-based roles: The base salary range for this role is USD$149,000 per year - USD$165,500 per year.
For San Francisco, CA-based roles: The base salary range for this role is USD$149,000 per year - USD$165,500 per year.