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가우스랩스 · 데이터·AI

  • 산업 AI·제조 데이터 분석
  • 2020년 설립 (7년차)

Data Science Manager - Manufacturing Data (KR)

Yeoksam, Seoul공식 채용 공고

이 브라우저에 저장돼요 · 최근 확인

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데이터·AI · 필수 · 경력 8년 이상 외 1개

주요 업무
  • Lead and develop data scientists through regular 1:1s, feedback, coaching, and performance management.
  • Support hiring, onboarding, and capability development for the team.
  • Set technical expectations and review data science, data engineering, and analytical work.
  • Help translate manufacturing and customer problems into technical plans, success criteria, and actionable analysis.
주요 업무 4개 더 보기
자격 요건
  • Bachelor’s degree in a technical or quantitative field, or equivalent practical experience.
  • 경력 조건8+ 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.
  • 경력 조건3+ 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.
자격 요건 3개 더 보기
우대 사항
  • 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.
근무·전형
  • Application review - Phone interview - Virtual onsite interview - Core Value interview - CEO interview

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가우스랩스, 어떤 회사일까요?

  • 산업 AI·제조 데이터 분석
  • 2020년 설립 (7년차)

제조 데이터와 AI를 결합해 공정 예측·계측을 지원하는 산업 AI 기업입니다. 2020년 미국에서 설립됐으며 서울과 팰로앨토 거점을 안내합니다.

가우스랩스 더 알아보기
포지션 소개 · 공고 전문 읽기

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

  • Lead and develop data scientists through regular 1:1s, feedback, coaching, and performance management.
  • Support hiring, onboarding, and capability development for the team.
  • Set technical expectations and review data science, data engineering, and analytical work.
  • Help translate manufacturing and customer problems into technical plans, success criteria, and actionable analysis.
  • Partner with Team Leads to align priorities, ownership, capacity, dependencies, and risks.
  • Work with Product, AI/ML, Software Engineering, SRE, and customer-facing teams to deliver integrated solutions.
  • Improve team practices for technical review, knowledge sharing, and continuous improvement.
  • Surface team and delivery risks early and communicate them clearly to relevant stakeholders.

Basic Qualifications

  • 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.

[Interview process]

Application review - Phone interview - Virtual onsite interview - Core Value interview - CEO interview