Senior Analyst, Data Science

Senior Analyst, Data Science (Applied AI, GenAI & Advanced Analytics) Dell Technologies is a leader in providing technology infrastructure to its customers in an era increasingly being driven by digital and data. Enabling Dell to satisfy its customers' needs hinges on executing a world class supply chain, connecting together sales orders with a complex ecosystem of partners and suppliers. Data plays an integral role in this as we digitize and modernize our supply chain. Join our Data science team within Supply chain as a data scientist to solve our most challenging business problems with statistical, predictive and prescriptive approaches, making our decision making faster and more sophisticated. We offer a competitive remuneration package. What you'll achieve: As a Senior Analyst, you will work with data scientists, engineers, and supply chain domain experts to translate business problems into data-driven solutions. Join us to do the best work of your career and make a profound social impact as a Senior Analyst, data science Team in Singapore. You will also: * Work with data scientists, engineers, and supply chain domain experts to translate business problems into data-driven solutions * Deliver end-to-end solutions for moderately complex problems, from data exploration to model deployment, with support from senior team members. * Use AI-assisted coding tools (e.g., Copilot, LLM-based tools) to improve productivity, while ensuring correctness and maintainability of generated code * Contribute to GenAI and agentic solutions, including building components such as prompt pipelines, retrieval systems, and evaluation workflows * Participate in experimentation and innovation initiatives, such as prototyping new approaches and applying emerging AI techniques to business problems * Collaborate with cross-functional teams to integrate models into production systems * Share learnings with peers and contribute to a data science community of practice * Continuously grow technical skills through a structured development plan Essential Requirements 1. 2 to 4 years of experience (or equivalent) in data science, ML, or analytics with a Bachelor's or Master's degree in Statistics, Computer Science, Engineering, Mathematics and experienced in: * LLM tools or platforms (e.g., Azure OpenAI or similar) * Basic RAG pipelines or embeddings * Working with large datasets in production environments 2. Applied Data Science & Solution Delivery * Develop, evaluate, and deploy machine learning and statistical models to solve business problems * Own well-defined problem areas end-to-end, including data preparation, modeling, and performance evaluation 3. GenAI & Emerging AI Techniques Hands-on implementation of GenAI components and workflows, including: * Prompt engineering * Retrieval-augmented generation (RAG) * Basic LLM-based workflows * Assist in developing agentic or multi-step AI workflows under guidance * Evaluate outputs for quality, relevance, and reliability 4. Coding Assist & Code Quality * Use coding-assist tools effectively to accelerate development * Review, debug, and maintain tool-generated code, ensuring quality and correctness * Write clean, well-documented, and testable code following software engineering best practices 5. Modeling & Analytics * Build supervised and unsupervised models including regression, classification, clustering, forecasting, and basic NLP * Perform exploratory data analysis and feature engineering on structured and unstructured datasets * Design and execute experiments (e.g., hypothesis testing, experimentation frameworks), select and tune models to optimize performance. 6. Data & Systems Integration * Query and process data from SQL and unstructured sources * Work with engineering teams to deploy models into production environments * Own model deployment with support from engineering or senior team members 7. Programming & Tools * Strong proficiency in Python * Familiarity with common data science libraries and workflows * Awareness of scalability and performance considerations 8. Innovation & Research * Contribute to innovation through experimentation, prototyping, and applying new techniques * Stay current with emerging trends in ML and GenAI, and apply them where relevant * Participate in team-level research or hackathon initiatives Desirable Requirements * Exposure to: + Model deployment (APIs, containers, or cloud platforms) + Cross-functional collaboration in delivering data Seni