
Senior Advisor, Data Science
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.
Join us to do the best work of your career and make a profound social impact as a Senior Advisor, data science Team in Singapore.
You will...
- Define and lead the technical vision and strategy for AI/ML and GenAI solutions across multiple teams or business domains
- Own and drive large, high-impact problem areas that are highly ambiguous, cross-functional, and critical to business success
- Architect enterprise-scale AI systems, including advanced GenAI platforms and agentic ecosystems
- Lead the adoption of emerging technologies and applied research, shaping how the organization leverages innovations in classical ML, optimization, simulation, causal inference, and GenAI
- Establish best practices for AI-assisted development, ensuring high standards for code quality, governance, and maintainability at scale
- Partner with senior business and engineering leaders to align AI investments with strategic priorities
- Drive innovation programs, incubation efforts, and research initiatives that unlock new capabilities and competitive advantage
- Mentor senior ICs (I6/I7) and act as a technical authority and escalation point for complex challenges
- Influence and shape organizational capabilities, hiring strategy, and technical standards
Essential Requirements
Bachelor's/Master's/PhD with 8-12+ years of experience in data science, ML, or applied AI
Strategic Technical Leadership
- Define technical direction and architecture for large-scale AI/ML and GenAI initiatives
- Translate business strategy into scalable AI solutions and platforms
- Influence decisions across teams, ensuring alignment with long-term architectural goals
Advanced Modeling & System Design
Demonstrated ability to lead the development of end-to-end AI/ML solutions, leveraging statistical modeling, machine learning, deep learning, optimization, forecasting, and anomaly detection techniques to solve complex business problems
Strong experience working with large-scale datasets using distributed computing frameworks such as Spark and Dask
Proven track record of architecting scalable and reliable ML platforms with integrated MLOps capabilities, ensuring reproducibility, governance, monitoring, and operational excellence
Provide guidance on advanced modeling techniques, including deep learning, optimization, simulation, demand forecasting, causal inference, and NLP
Ensure appropriate trade-offs between model complexity, performance, and maintainability
Design systems with reusability, modularity, and platform thinking
Balance classical statistical and ML techniques with modern GenAI approaches based on problem fit and domain relevance.
Classical Techniques, Optimization & Domain Analytics
Champion the use of classical techniques - optimization, simulation, demand forecasting, causal inference, and experimentation design - as foundational capabilities of the team
Ensure advanced analytics solutions address core supply chain problems such as demand planning, inventory optimization, logistics, and operational decision-making
Drive the adoption of prescriptive and causal approaches alongside predictive and generative methods
GenAI & Agentic Systems (Expert-Level Expectation)
Architect and oversee development of advanced Generative AI systems, including:
Enterprise-scale RAG architectures
Multi-agent systems and orchestration frameworks
LLM fine-tuning, evaluation, and optimization strategies
Establish standards, guardrails, and governance frameworks for responsible GenAI use
Drive adoption of agentic AI capabilities to enable intelligent automation and decision systems
Innovation & Research Leadership
Lead applied research and innovation strategy across teams
Identify emerging technologies and translate them into scalable, production-ready solutions
Establish and drive innovation programs, research agendas, and incubation efforts
Encourage experimentation while ensuring clear pathways to production and business impact
Champion innovation across both classical methods (optimization, simulation, causal inference) and modern AI techniques
Coding Assist & Engineering Excellence at Scale
Define and enforce best practices for AI-assisted coding and development workflows
Ensure teams effectively:
Use coding-assist tools responsibly
Review and maintain AI-generated code rigorously
Champion engineering excellence, including testing, CI/CD, observability, and scalability
Advanced Modeling & System Design
Provide guidance on advanced modeling techniques, including deep learning, optimization, forecasting, and NLP
Ensure appropriate trade-offs between model complexity, performance, and maintainability
Design systems with reusability, modularity, and platform thinking
Data, Platform & Ecosystem Integration
Oversee integration of AI systems into enterprise data platforms and distributed architectures
Ensure systems meet requirements for:
Scalability
Reliability
Security and governance
Drive adoption of MLOps / LLMOps practices across teams
Organizational Influence & Mentorship
Mentor and coach senior data scientists (I6/I7)
Lead design and architecture reviews
Influence organizational capability building, hiring, and technical standards
Desirable Requirements
Proven track record of:
- Leading large-scale, cross-functional AI initiatives
- Defining and executing AI/GenAI strategies
- Delivering enterprise-grade AI systems in production
Deep experience with:
- LLM ecosystems (e.g., Azure OpenAI, open-source models)
- Agentic frameworks and orchestration tools
- Vector databases and large-scale data systems
- Optimization solvers, simulation tools, or causal inference frameworks
- Distributed computing frameworks such as Spark and Dask
Nice to Have (Advanced Expertise Areas)
Experience in supply chain, operations research, demand forecasting, inventory optimization or enterprise optimization domains.
Contributions to research publications, patents, or thought leadership
Experience influencing executive-level decision-making and strategy
Strong familiarity with responsible AI, governance, and compliance frameworks
Advanced AI Data Systems Knowledge
Understanding of agentic memory architectures, including short-term, long-term, and episodic memory patterns in AI agents
Hands-on experience or familiarity with vector databases (e.g., embeddings storage, similarity search, RAG optimization)
Knowledge of graph databases and graph-based reasoning, including knowledge graphs, entity relationships, and their use in AI/GenAI systems
Ability to combine vector, graph, and memory-based approaches to design richer, context-aware AI systems
Hands-on experience with MCP (Model Context Protocol) and A2A (Agent-to-Agent communication)
Experience integrating AI/ML and LLM Observability and Monitoring tools
Who we are
We believe that each of us has the power to make an impact. That's why we put our team members at the center of everything we do. If you're looking for an opportunity to grow your career with some of the best minds and most advanced tech in the industry, we're looking for you.
Dell Technologies is a unique family of businesses that helps individuals and organizations transform how they work, live and play. Join us to build a future that works for everyone because Progress Takes All of Us.
Dell Technologies is committed to the principle of equal employment opportunity for all employees and to providing employees with a work environment free of discrimination and harassment. Read the full Equal Employment Opportunity Policy here.
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