Purpose & Scope: 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.

Essential Duties & Responsibilities

What you will be doing (responsibilities):

. Own E2E Data Science/AI solutions including building out timelines/key milestones, prioritization, providing

regular updates to product managers, analytics management and delivery against agreed timelines.

. Lead the identification of machine learning opportunities and design end-to-end solutions.

. Develop sophisticated machine learning models, including deep learning, recommendation systems, and natural

language processing.

. Guide the deployment and monitoring of models in production environments, ensuring robustness, scalability,

and performance.

. Design experiments, perform hypothesis testing, and evaluate model impact on business KPIs.

. Collaborate with business, engineering, and product teams to integrate AI/ML solutions into business workflows.

. Contribute to the data science & AI roadmap, advocating for AI/ML best practices and data-driven culture.

Experience, Skills & Knowledge

What you bring (Qualifications):

Education & Experience:

. Master's 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).

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Senior Data Scientist