Data Science Manager - Manufacturing Data (KR)
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Before you apply
LocationYeoksam, Seoul
Work modehybrid
Typefull-time
SeniorityLead
Experience8+ yrs
Department1. Tech, Manufacturing Data
Company size51–200 people
PostedOct 28, 2026 · 1w ago
Verified live12h ago
At a glanceSummarised by Seekless from the posting.
Bachelor’s degree in a technical or quantitative field, or equivalent practical experience
8+ years of related experience in data science, applied machine learning, analytics, data engineering, or a related technical discipline, including substantial hands-on data science experience
3+ years of experience leading or managing technical professionals and supporting their career growth
Strong technical judgment in data science, including problem framing, statistical analysis, evaluation design, and interpretation of results; able to review analytical and modeling approaches and guide trade-offs
Demonstrated ability to turn ambiguous problems into clear plans and outcomes
Strong communication and collaboration skills across teams and functions
Experience in semiconductor manufacturing, industrial AI, or manufacturing data
Experience delivering data science or AI solutions in customer or production environments
Familiarity with feature engineering, model evaluation, or manufacturing process analytics
Experience building team practices, hiring plans, or technical career development paths
Professional Korean and working English (confirm based on customer and team needs)
About the role
The Data Science Manager leads and develops a team working at the intersection of manufacturing, data science, and AI. You will help the team understand customer and product needs, guide technical approaches, and deliver reliable solutions for manufacturing use cases. This is a hands-on leadership role: you will combine people management with technical judgment while partnering closely with Team Leads and cross-functional teams.
Responsibilities
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Lead and develop data scientists through regular 1:1s, feedback, coaching, and performance management.
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Support hiring, onboarding, and capability development for the team.
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Set technical expectations and review data science, data engineering, and analytical work.
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Help translate manufacturing and customer problems into technical plans, success criteria, and actionable analysis.
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Partner with Team Leads to align priorities, ownership, capacity, dependencies, and risks.
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Work with Product, AI/ML, Software Engineering, SRE, and customer-facing teams to deliver integrated solutions.
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Improve team practices for technical review, knowledge sharing, and continuous improvement.
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Surface team and delivery risks early and communicate them clearly to relevant stakeholders.
Basic Qualifications
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Bachelor’s degree in a technical or quantitative field, or equivalent practical experience.
•
8+ years of related experience in data science, applied machine learning, analytics, data engineering, or a related technical discipline, including substantial hands-on data science experience.
•
3+ years of experience leading or managing technical professionals and supporting their career growth.
•
Strong technical judgment in data science, including problem framing, statistical analysis, evaluation design, and interpretation of results; able to review analytical and modeling approaches and guide trade-offs.
•
Demonstrated ability to turn ambiguous problems into clear plans and outcomes.
•
Strong communication and collaboration skills across teams and functions.
•
Professional Korean and working English (confirm based on customer and team needs).
Preferred Qualifications
•
Experience in semiconductor manufacturing, industrial AI, or manufacturing data.
•
Experience delivering data science or AI solutions in customer or production environments.
•
Familiarity with feature engineering, model evaluation, or manufacturing process analytics.
•
Experience building team practices, hiring plans, or technical career development paths.
Hiring process
[Interview process]
Application review - Phone interview - Virtual onsite interview - Core Value interview - CEO interview