Top AI & Machine Learning Jobs

The Applied Scientist will develop quantitative models to improve pricing, demand forecasting, and risk management, collaborating with cross-functional teams to implement solutions.

As an Applied Scientist, you will develop quantitative models for decision-making in pricing, resale strategy, and risk management, involving hands-on coding and collaboration with other teams.

The Applied Scientist role involves developing quantitative models for decision-making under uncertainty, focusing on pricing, demand modeling, and risk management. Responsibilities include building and optimizing models, collaborating with engineering and product teams, and translating complex problems into actionable solutions.

Lead design and implementation of MLOps platforms for pricing: productionize models, own end-to-end pipelines (ingest, training, deployment, monitoring), optimize data access and SQL, automate retraining and releases, improve reliability and observability, mentor engineers, and participate in on-call incident response.

As an Applied Scientist, you'll develop and deploy ML models, enhance pricing systems, and work with structured and unstructured data to improve decision-making.

The Applied Scientist will tackle various machine learning problems, enhance valuation systems, and deploy deep learning models while collaborating with cross-functional teams.

As an Applied Scientist, you will push the limits of AI/ML in home valuation, tackling diverse ML challenges and optimizing decision-making with data.

As a Data Scientist at Opendoor, you'll enhance pricing strategies through statistical models, machine learning, experiments, and interdisciplinary collaboration to drive business outcomes.