Dell Technologiesは、シンガポールのグローバルOpsチームでデータサイエンス・アドバイザーを募集しています。特徴量エンジニアリングおよびMLエンジニアリングの専門知識を活かし、ML/GenAIシステム向けの拡張可能なパイプラインを構築します。5〜8年以上の経験とデータエンジニアリングのスキルが必須です。複雑なサプライチェーンの課題を解決し、技術的なリーダーシップを発揮できる方を求めています。
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 an Advisor, data science Team in Singapore.
Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field with 5–8 years of experience in ML engineering, data engineering, or data science, with a strong focus on feature engineering
Feature Engineering & Data Discovery (Core Focus)
Lead feature identification and engineering across:
Structured data (SQL, data warehouses, relational systems)
Unstructured data (text, logs, documents, semi-structured sources)
Perform deep exploratory data analysis (EDA) to uncover patterns, anomalies, and predictive signals
Apply advanced techniques:
Feature extraction, transformation, and scaling
Embeddings and representation learning
Feature selection and dimensionality reduction
Strong foundation in software engineering practices, including:
Writing production-quality, modular, testable code
API and service development (for feature serving)
Version control, CI/CD, and system reliability
Design and implement feature pipelines as scalable systems, not just scripts
Build and maintain data/feature services for both batch and real-time use cases
Collaborate on model training and inference pipelines, ensuring seamless integration
Develop features for NLP and GenAI applications, including:
Text preprocessing, tokenization, and normalization
Embedding generation and similarity search features
Support and enhance RAG pipelines and LLM-based workflows with high-quality data representations
Contribute to agentic systems, especially around context construction, state, and data grounding
Build scalable and reusable feature pipelines using modern data processing frameworks
Ensure pipelines are:
Fault-tolerant and performant
Observable and testable
Implement efficient data transformations for large-scale datasets
In-depth hands-on experience in Enterprise Database Management
Experience with Airflow data pipelines for orchestrating and scheduling feature and data workflows
Use AI-assisted coding tools to enhance productivity
Critically review and validate tool-generated code, ensuring correctness, efficiency, and security
Maintain high standards of code quality, testing, and documentation
Implement robust data validation and feature quality checks
Monitor:
Data consistency
Feature drift
Pipeline health
Ensure traceability and reproducibility of features used across models
Act as a bridge between data science and ML engineering, aligning feature design with modeling needs
Provide technical leadership on feature engineering best practices
Mentor I5/I6 team members and contribute to design and code reviews
Drive innovation in:
Feature engineering frameworks and tooling
Data-centric AI and representation learning
Experiment with and adopt emerging approaches in GenAI, embeddings, and feature stores
Lead or contribute to prototyping and innovation initiatives
Building production-grade data pipelines and feature systems
Applying software engineering best practices to data/ML systems
Working with large-scale structured and unstructured date
Feature stores (Feast, Tecton, or similar)
Vector databases and embedding pipelines
Graph databases and knowledge graphs
Enterprise database management systems
Airflow or similar workflow orchestration tools
Agentic memory architectures (short-term, long-term, contextual memory)
Combining vector, graph, and memory-based approaches for richer AI systems
MLOps / LLMOps practices
Real-time feature serving architectures
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.
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.
Visit our Culture Code page to learn more about how we work and lead.
