Dell

3 weeks ago

Advisor, Data Science (Feature engineer) - Global Ops Data Science

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 50 minutes agoStatus: Live

Job Summary

Build and productionize end-to-end features that power ML and GenAI systems for Dell’s supply chain organization. Partner with data scientists and ML engineers to discover signals in structured and unstructured data, lead feature engineering and validation, and design scalable feature pipelines and services for batch and real-time decisioning. Contribute to NLP/GenAI feature development (embeddings, representation learning, RAG workflows) while using software engineering practices and AI-assisted coding tools.

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Partner with data scientists, ML engineers, and domain experts to design and deliver high-quality features powering ML and GenAI systems.
•Lead data discovery and feature identification across complex structured and unstructured datasets.
•Own the end-to-end feature engineering lifecycle, including ingestion, transformation, validation, and productionization.
•Design and implement robust, scalable feature pipelines and services using software engineering principles for reliability, performance, and maintainability.
•Mentor junior team members and help establish best practices for feature development and data engineering.

Key Requirements

•Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field with 5–8 years of experience in ML engineering, data engineering, or data science focused on feature engineering.
•Strong feature engineering and data discovery skills across structured (SQL, data warehouses, relational systems) and unstructured data (text, logs, documents).
•Experience with feature extraction, transformation, scaling, embeddings/representation learning, and feature selection/dimensionality reduction.
•Strong software engineering practices for ML systems, including production-quality modular testable code, API/service development, and CI/CD with reliability.
•Hands-on experience building scalable feature pipelines/services for batch and real-time use cases, plus collaboration on training and inference pipelines.

Experience:5-8 yearsSupply chainGenAIML engineeringData engineering

Education:Master's

Skills:CollaborationTechnical leadershipMentoringInnovationCode quality

Tech Stack:SQLData warehousesAPIsCI/CDCopilotLLM-based toolsEmbeddingsRepresentation learningFeature selectionDimensionality reductionNLPGenAIRAGLLM-based workflowsFeature pipelinesFeature servingText preprocessingTokenizationNormalizationSimilarity search

Company Brief

Dell

Designs, manufactures and sells computers, servers, storage, networking equipment, and related IT solutions and services for consumers, small businesses, and enterprises worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Round Rock, United States

Founded: 1984

Glassdoor: 3.8

Website LinkedIn Glassdoor

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Dell

3 weeks ago

Advisor, Data Science (Feature engineer) - Global Ops Data Science

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 50 minutes agoStatus: Live

Job Summary

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Partner with data scientists, ML engineers, and domain experts to design and deliver high-quality features powering ML and GenAI systems.
•Lead data discovery and feature identification across complex structured and unstructured datasets.
•Own the end-to-end feature engineering lifecycle, including ingestion, transformation, validation, and productionization.
•Design and implement robust, scalable feature pipelines and services using software engineering principles for reliability, performance, and maintainability.
•Mentor junior team members and help establish best practices for feature development and data engineering.

Key Requirements

•Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field with 5–8 years of experience in ML engineering, data engineering, or data science focused on feature engineering.
•Strong feature engineering and data discovery skills across structured (SQL, data warehouses, relational systems) and unstructured data (text, logs, documents).
•Experience with feature extraction, transformation, scaling, embeddings/representation learning, and feature selection/dimensionality reduction.
•Strong software engineering practices for ML systems, including production-quality modular testable code, API/service development, and CI/CD with reliability.
•Hands-on experience building scalable feature pipelines/services for batch and real-time use cases, plus collaboration on training and inference pipelines.

Experience:5-8 yearsSupply chainGenAIML engineeringData engineering

Education:Master's

Skills:CollaborationTechnical leadershipMentoringInnovationCode quality

Company Brief

Dell

Designs, manufactures and sells computers, servers, storage, networking equipment, and related IT solutions and services for consumers, small businesses, and enterprises worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Round Rock, United States

Founded: 1984

Glassdoor: 3.8

Website LinkedIn Glassdoor