Destination Science Jobs in New York (NOW HIRING)

Rent the Runway (RTR) is transforming the way we get dressed by pioneering the world's first Closet in the Cloud. Founded in 2009, RTR has disrupted the $2.4 trillion fashion industry by inspiring women with a more joyful, sustainable and financially-savvy way to feel their best every day. As the ultimate destination for circular fashion, the brand now offers infinite points of access to its shared closet via a fully customizable subscription to fashion, one-time rental or ownership. RTR offers designer apparel and accessories from hundreds of brand partners and has built in-house proprietary technology and a one-of-a-kind reverse logistics operation. RTR has been named to CNBC’s "Disruptor 50" five times in ten years, and has been placed on Fast Company’s Most Innovative Companies list multiple times.

Data is core to our growing business and has been ingrained in the company's DNA since its founding. As a member of the Data Analytics team, you will partner closely with Product, Engineering, and other business stakeholders to identify opportunities where machine learning, AI, and advanced analytics can create meaningful customer and business value.

The Data Science team develops machine learning solutions, recommendation systems, experimentation frameworks, and AI-powered capabilities that directly influence how customers discover, engage with, and rent and buy inventory on Rent the Runway. Our work spans personalization, predictive modeling, decision systems, and intelligent customer experiences.

As RTR continues investing in personalization and AI, Data Science plays a critical role in bringing new customer experiences to life - from recommendation engines and intelligent styling and fit experiences to future agent-driven and AI-powered products.

We are looking for a hands‑on Data Science Manager to lead our growing Data Science function while remaining deeply involved in solving high-impact machine learning problems. While this role will initially focus on personalization, recommendation systems, and AI-powered customer experiences, you will also have the opportunity to contribute across a broad range of high-impact machine learning initiatives as business priorities evolve.

As the technical leader and manager of the Data Science team, you will partner closely with Product, Engineering, and business stakeholders to translate ambiguous business problems into scalable, production-ready machine learning solutions that directly improve customer experience and business outcomes. You will provide technical direction, mentor Data Scientists, help prioritize the team's work, and help shape the long-term evolution of Data Science at Rent the Runway.

This is a hands‑on leadership role. You will be expected to remain actively involved in designing, building, and reviewing machine learning solutions while coaching and growing a high-performing Data Science team.

We're looking for someone with strong technical expertise, product intuition, analytical rigor, leadership skills, and the ability to operate independently in a fast-paced environment.

• Lead, coach, and develop the Data Science team, providing technical guidance, feedback, and career development while fostering a high-performing, collaborative culture.
• Define the technical direction and priorities of the Data Science function, ensuring work is aligned with business strategy and delivers measurable customer impact.
• Lead strategic data science initiatives by partnering closely with cross‑functional teams to identify, scope, and solve complex business problems.
• Analyze customer, product, and inventory data to identify high-impact opportunities where machine learning and AI can improve customer and business outcomes.
• Partner closely with Product and Engineering to identify customer problems, shape product strategy, and bring intelligent, AI-powered customer experiences to life.
• Design, build, deploy, and continuously improve recommendation systems, personalization solutions, and ranking models that enhance customer engagement, conversion, and retention.
• Design and analyze experiments, A/B tests, and causal inference frameworks to measure product and business impact.
• Develop customer similarity models, behavioral segmentation, and ranking approaches to improve personalization throughout the customer journey.
• Partner across Product, Engineering, and the broader Data organization to deliver scalable, production-ready machine learning solutions.
• Help shape hiring strategy, evaluate talent, and build a high-performing Data Science organization as the team continues to grow
• Communicate insights, trade‑offs, and recommendations clearly to both technical and non-technical stakeholders, including executive leadership.
• Drive best practices across the Data & Analytics organization around experimentation, statistical rigor, model governance, and machine learning development.

• 7+ years of hands‑on experience in Data Science, Machine Learning, Applied Statistics, Product Analytics, or a related quantitative field - or equivalent combination of education and experience - including 2+ years leading Data Science teams or technical initiatives, or demonstrated experience providing technical mentorship and project leadership in a collaborative team environment.
• Bachelor's degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Economics, Physics, Operations Research), or equivalent practical experience; advanced degrees and/or specializations are a plus.
• Experience leading, mentoring, or managing Data Scientists or other technical professionals.
• Strong proficiency in Python and experience developing predictive, statistical, or machine learning models.
• Strong proficiency in SQL, with the ability to write efficient and optimized queries against large-scale datasets.
• Strong foundation in statistics, experimentation, hypothesis testing, and causal inference.
• Proven relevant experience designing, building, and deploying recommendation systems, personalization solutions, ranking models, customer segmentation frameworks, or similar machine learning applications.
• Demonstrated ability to provide technical leadership while balancing hands‑on machine learning work with coaching, mentoring, and people management.
• Strong expertise with cloud AI/ML platforms and services (e.g., GCP, AWS, or Azure), including experience deploying, fine‑tuning, and optimizing managed models. Experience with GCP is a strong plus.
• Experience working with large-scale datasets in BigQuery, Snowflake, or similar cloud data platforms. Familiarity with dbt and modern analytics engineering practices is a plus.
• Demonstrated ability to independently lead complex projects from problem definition through implementation and stakeholder communication.
• Ability to communicate effectively