Machine Learning Engineer, Growth at Metropolis… · New York

Summary: Metropolis Technologies is pioneering the Recognition Economy with innovative artificial intelligence solutions. They are seeking a Machine Learning Engineer to develop and enhance revenue forecasting and dynamic pricing systems, playing a critical role in influencing key business metrics through model design and implementation. Responsibilities: - Design, develop, and productionize demand forecasting models optimized for different business goals (e.g., visits, revenue, availability) - Innovate and improve Machine Learning models for price elasticity, time series, and probabilistic models for revenue optimization - Design and build end-to-end data pipelines to support large-scale production usage - Identify data issues (e.g., bias, leakage, labeling inconsistencies) and drive solutions - Design and analyze experiments (A/B, switchback, causal inference) to validate pricing strategies - Deploy and monitor models in production, ensuring reliability, scalability, and data quality - Collaborate with product, engineering, and business teams to translate requirements into scalable ML solutions Required Qualifications: - PhD in Computer Science, Statistics, Economics, Applied Mathematics, or a related STEM field, with at least 1+ years of relevant experience, or MS with equivalent publications - Proficient programming skills in Python and SQL - Foundational experience in machine learning modeling and statistics, such as time series forecasting, probabilistic models, and deep learning models - Strong knowledge with forecasting, optimization, and decision-making algorithms, including revenue maximization, constrained optimization, and demand/price curve optimization - Solid understanding of causal inference and experimentation, with experience evaluating both short-term and long-term effects (A/B testing, DiD, uplift modeling) - Hands-on experience with data pipeline development, including AWS data storage, data transformation, distributed processing (Spark), and workflow orchestration (Airflow) - Strong communication skills, both written and verbal, with the ability to operate effectively at team and deep technical levels - Comfortable reading academic papers and formulating concepts using mathematical notation Required Skills: Machine Learning, Python, SQL Important Skills: Data Pipeline Development, Causal Inference, Time Series Forecasting Benefits: Healthcare benefits, A 401(k) plan, Short-term and long-term disability coverage, Basic life insurance, A lucrative stock option plan, Bonus plans