Advisor, Data Science

Advisor, Data Science (Feature engineer) - Global Ops 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 an Advisor, data science Team in Singapore.

You will...
1.

Partner closely with data scientists, ML engineers, and domain experts to design and deliver high-quality features that power ML and GenAI systems
2.

Lead data discovery and feature identification efforts across complex structured and unstructured datasets
3.

Own the end-to-end feature engineering lifecycle, including ingestion, transformation, validation, and productionization
4.

Design and implement robust, scalable feature pipelines and services using strong software engineering principles
5.

Bring a software engineering (ML engineering) mindset to data and feature development, ensuring reliability, performance, and maintainability
6.

Leverage AI-assisted coding tools (e.g., Copilot, LLM-based tools) while maintaining high standards of code review, correctness, and efficiency
7.

Drive innovation in feature engineering, including embeddings, representation learning, and data-centric AI approaches
8.

Work with ML engineers to integrate features into training, inference, and real-time decision systems
9.

Mentor junior team members and help establish best practices in feature development and data engineering

Essential Requirements
1.

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

2.

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

3.

ML Engineering & Software Engineering Excellence



* Strong foundation in software engineering practice...