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About the Role

Rent the Runway is seeking a hands-on Data Science Manager to lead the Data Science function, focusing initially on personalization, recommendation systems, and AI-powered customer experiences. This role involves technical leadership, mentoring Data Scientists, and driving the development of scalable machine learning solutions to enhance customer experience and business outcomes.

Responsibilities

• 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.

Requirements

• 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.
• 2+ years leading Data Science teams or technical initiatives, or demonstrated experience providing technical mentorship and project leadership in a collaborative team environment.
• 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 working with large-scale datasets in BigQuery, Snowflake, or similar cloud data platforms.
• Demonstrated ability to independently lead complex projects from problem definition through implementation and stakeholder communication.
• Ability to communicate effectively with a wide range of audiences, including business stakeholders, product managers, engineers, and executive leadership.
• Extremely curious and excited to dive into complex problems.
• Self-driven, proactive, and comfortable operating with ownership and ambiguity.

Skills

• Data Science
• Machine Learning
• Applied Statistics
• Product Analytics
• Python
• SQL
• Statistics
• Experimentation
• Hypothesis Testing
• Causal Inference
• Recommendation Systems
• Personalization
• Ranking Models
• Customer Segmentation
• Cloud AI/ML platforms (GCP, AWS, Azure)
• BigQuery
• Snowflake
• dbt
• Analytics Engineering

Location

• Remote (Fridays)

Work Type

• Office-centric
• Remote (Fridays)

Experience Level

• Manager
• 7+ years
• 2+ years leadership

Education Level

• 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

Salary/Compensations

• $138,400 to $177,435

Benefits

• Paid Time Off, including vacation, paid bereavement, and family sick leave
• Comprehensive health, vision, dental, FSA and dependent care from day 1 of employment
• 401(k) match
• Exclusive employee subscription and rental discounts
• Universal Paid Parental Leave for both parents + flexible return to work program
• Paid Sabbatical after 5 years of continuous service
• Company-wide events and outings

About the Company

• 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.

Equal Opportunity

• Rent the Runway is an equal opportunity employer. In accordance with applicable law, we prohibit discrimination against any applicant or employee based on any legally-recognized basis, including, but not limited to: race, color, religion, sex (including pregnancy, lactation, childbirth or related medical conditions), sexual orientation, gender identity, age (40 and over), national origin or ancestry, citizenship status, physical or mental disability, genetic information (including testing and characteristics), veteran status, uniformed service member status or any other status protected by federal, state or local law.