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 solutionsDeliver 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 codeContribute to GenAI and agentic solutions, including building components such as prompt pipelines, retrieval systems, and evaluation workflowsParticipate in experimentation and innovation initiatives, such as prototyping new approaches and applying emerging AI techniques to business problemsCollaborate with cross-functional teams to integrate models into production systemsShare learnings with peers and contribute to a data science community of practiceContinuously grow technical skills through a structured development planEssential Requirements1. 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 embeddingsWorking with large datasets in production environments2. Applied Data Science & Solution DeliveryDevelop, evaluate, and deploy machine learning and statistical models to solve business problemsOwn well-defined problem areas end-to-end, including data preparation, modeling, and performance evaluation3. GenAI & Emerging AI TechniquesHands-on implementation of GenAI components and workflows, including:Prompt engineeringRetrieval-augmented generation (RAG)Basic LLM-based workflowsAssist in developing agentic or multi-step AI workflows under guidanceEvaluate outputs for quality, relevance, and reliability4. Coding Assist & Code QualityUse coding-assist tools effectively to accelerate developmentReview, debug, and maintain tool-generated code, ensuring quality and correctnessWrite clean, well-documented, and testable code following software engineering best practices5. Modeling & AnalyticsBuild supervised and unsupervised models including regression, classification, clustering, forecasting, and basic NLPPerform exploratory data analysis and feature engineering on structured and unstructured datasetsDesign and execute experiments (e.g., hypothesis testing, experimentation frameworks), select and tune models to optimize performance.6. Data & Systems IntegrationQuery and process data from SQL and unstructured sourcesWork with engineering teams to deploy models into production environmentsOwn model deployment with support from engineering or senior team members7. Programming & ToolsStrong proficiency in PythonFamiliarity with common data science libraries and workflowsAwareness of scalability and performance considerations8. Innovation & ResearchContribute to innovation through experimentation, prototyping, and applying new techniquesStay current with emerging trends in ML and GenAI, and apply them where relevantParticipate in team-level research or hackathon initiativesDesirable RequirementsExposure to model deployment (APIs, containers, or cloud platforms) and cross-functional collaboration in delivering data productsFamiliarity with MLOps / LLMOps concepts. Experience in supply chain, logistics, or operations analytics. Familiarity with MLOps / LLMOps concepts. Participation in innovation initiatives, hackathons, or applied research projects