Rent the Runway (RTR) is transforming the way we get dressed by pioneering the world's first Closet in the Cloud. The Data Science team extracts meaning from RTR's many rich customer interactions and partners with decision-makers across Product, Inventory, and Operations to turn insights into action. The team defines and analyzes performance metrics, runs A/B experiments, and develops and deploys machine learning models that power customer experiences and drive operational efficiency.
Requirements
- 3-5+ years of hands-on experience building and deploying machine learning models in production.
- Demonstrated experience in areas like recommendation systems, personalization, or ranking models.
- Strong proficiency in Python and core ML libraries (Scikit-learn, Pandas, NumPy, XGBoost) as well as deep learning frameworks (PyTorch).
- High proficiency using relational databases and writing queries in SQL.
- Hands-on experience productionizing models on GCP, with specific expertise in Vertex AI, is strongly preferred.
Responsibilities
- Design, develop, and deploy scalable ML models in areas like recommendation, personalization, and inventory optimization.
- Own the full ML lifecycle: data preparation, model training, validation, deployment, and monitoring.
- Build and maintain robust feature pipelines and model monitoring systems.
- Collaborate with Product teams to design, implement, and analyze A/B tests for both ML-driven and standard product features.
- Partner with cross-functional teams to measure and communicate business impact.
- Define and track key performance metrics for model accuracy, reliability, and relevance.
- Design, build, and deploy the machine learning models that shape RTR's customer experience and business strategy.
Other
- Bachelor's degree in a quantitative field like Computer Science, Statistics, Mathematics, or Engineering; an advanced degree (MS or PhD) is a strong plus.
- Track record of building strong relationships with cross-functional partners.
- Ability to communicate effectively with wide-range of audiences.
- The actual base salary offered will depend on a variety of factors, including without limitation, the qualifications of the individual applicant for the position, years of relevant experience, level of education attained, certifications or other professional licenses held.
