The Senior Data Scientist role is a hands-on technical IC (Individual Contributor) role within the Data Science & AI team, driving the design, development, and deployment of scalable machine learning and AI solutions for complex business challenges.

This role will require execution of E2E data science & AI initiatives, owning the delivery roadmap and collaboration with cross-functional stakeholders to drive data-driven transformation across Ralph Lauren.

JOB DESCRIPTION :

- Lead end-to-end measurement for AI systems, aligning metrics with business outcomes, user experience, and trustworthiness

Experience, Skills & Knowledge :

Education & Experience :

- Masters degree in data science, computer science, applied mathematics, statistics, or a related quantitative field.

- 6-9 years of professional experience in advanced analytics and machine learning roles.

- Experience in analyzing complex and ambiguous business problems and translating them into data science/AI solutions.

- Strong expertise in Python, SQL, and experience with big data processing tools (Spark, Hadoop). Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, Keras).

- Experience in machine learning, supervised and unsupervised learning : Natural Language Processing (NLP), classification algorithms, advanced data/text mining techniques, multi-modal model development, and deep neural network architecture.

- Experience in statistical learning methodologies including but not limited to Predictive & Prescriptive Analytics, Web Analytics, Parametric and Non-parametric models, Regression, Time Series Forecasting, Market Basket Analysis, Dynamic/Causal Inference Modeling, Statistical Learning, Guided Decisions, Topic Modeling

- Familiarity with Autonomous AI systems design, implementation of human-in-the-loop frameworks, and expertise in AI system monitoring, observability and governance practices.

- Experience in end-to-end LLM implementation including custom embedding generation, vector database management, LLM gateway configuration, RAG-based agent development, strategic model selection, iterative prompt refinement, model fine-tuning for accuracy optimization, and implementation of robust monitoring and governance frameworks.

- Proficiency in modern orchestration frameworks such as LangChain or DSPy.

- Experience in MLOps best practices, including production-grade model deployment at scale, and designing/implementing enterprise-level AI/ML governance structures.

- Expert communication and collaboration skills with the ability to work effectively with internal teams in a cross cultural and cross-functional environment. Ability to communicate conclusions to both tech and non-tech audiences

Desired Skills :

- Retail industry experience and an understanding of retail/ecommerce data landscapes are strong pluses.

- Expertise in model interpretability techniques and ethical/responsible AI considerations.

- Familiarity with DevOps/DataOps practices for CI/CD of machine learning pipelines.

- Familiarity with Graph DB architecture.

- Proficiency in cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes)