Gauss Labs

Industrial AI for semiconductor manufacturing optimization

Data Science Manager - Manufacturing Data

Data ScienceConfirmed live in the last 24 hours

Full-timeSeoul, South KoreaNo salary listedHybrid

About the Job

Requirements

A bachelor's degree in a technical or quantitative field, or equivalent practical experience.
At least 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.
At least 3 years of experience leading or managing technical professionals and supporting their career growth.
Strong data science technical judgment, including problem framing, statistical analysis, evaluation design, interpretation of results, review of analytical and modeling approaches, and guidance on trade-offs.
Demonstrated ability to turn ambiguous problems into clear plans and outcomes.
Professional Korean and working English, depending on customer and team needs.

Responsibilities

Lead and develop data scientists through regular one-on-one meetings, 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.
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, site reliability engineering, and customer-facing teams to deliver integrated solutions.
Improve team practices for technical review, knowledge sharing, and continuous improvement.
Identify team and delivery risks early and communicate them clearly to relevant stakeholders.

Desired 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.

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

About the Company

Gauss Labs

Industrial AI for semiconductor manufacturing optimization

Gauss Labs builds AI-powered software for manufacturing, with a focus on the semiconductor sector. Its products monitor and optimize factory processes by collecting machine-generated data from production lines and running AI models on scalable software infrastructure to detect anomalies, improve quality, and reduce downtime. The company differentiates itself through deep domain expertise in industrial AI, a leadership team with a background in enterprise ML and product development, and a cross‑border presence in Silicon Valley and Seoul to serve large manufacturing customers with enterprise-grade solutions. The goal is to make semiconductor factories more efficient and reliable by turning data into actionable insights and automated process improvements.

Company size: 51-200
Company stage: Late Stage VC
Total funding: $55M
Headquarters: Palo Alto, CA
Founded: 2020

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