Company Overview :

Nykaa is India’s leading beauty and lifestyle destination, operating on an omnichannel model with a strong online presence and an expanding network of retail stores. We offer a comprehensive selection of beauty, skincare, hair care, wellness, and fashion products, catering to millions of customers across the country. Nykaa is committed to providing a curated, personalized, and seamless shopping experience through cutting-edge technology and data-driven insights.

Role Overview :

As a Product Manager – Personalization at Nykaa, you will be responsible for the end-to-end execution of features that power our discovery and recommendation engines. This is a product role where you will sit at the intersection of user behavior, fashion trends, and machine learning. You will work closely with Data Science and Engineering teams to build, test, and iterate on models that make the shopping journey uniquely relevant for every user. You will be based in our Gurgaon/Gurugram office.

Key Responsibilities :

• Model & Feature Execution: Work daily with Data Science and Engineering teams to translate high-level objectives into detailed PRDs, technical specifications, and model requirements.
• Data Science Collaboration: Partner with DS pods to refine ranking logic, collaborative filtering, and computer vision attributes to improve recommendation quality and relevance.
• Market & Technical Research: Conduct deep-dive research into global fashion-tech benchmarks and ML-driven commerce models to identify opportunities for innovation in sizing, fit, and style discovery.
• Experimental Rigor: Design and manage a high-velocity A/B testing pipeline. Analyze results to validate hypotheses and determine the production-readiness of new algorithms.
• Cross-functional Alignment: Coordinate with Category, Design, and QA teams to ensure seamless integration of data-driven features into the Nykaa Fashion UI/UX.

Required Skillset :

• Academic Background: Bachelor’s or Master’s degree from a Tier 1 institution with a strong analytical or technical foundation.
• Technical Fluency: Hands-on experience working with Data Science teams. You should be comfortable discussing model performance, data pipelines, and API integrations.
• Analytical Depth: Strong analytical and problem-solving skills, with the ability to use data to inform product decisions and measure product performance.
• Product Thinking: A strong sense of user empathy combined with the ability to break down complex problems into actionable product requirements.
• Communication: Ability to bridge the gap between technical complexity and business impact, ensuring all stakeholders are aligned on the "why" behind the "what."