The Specific Pay Range For A Preferred Location

DataScientist(GlobalManufacturingAnalytics)

$130–210k ~AI est. Penang, Malaysia FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Data Scientist (Global Manufacturing Analytics) at The Specific Pay Range For A Preferred Location. Skills: Data science, Machine learning, AI modeling, Business intelligence. Deliver data-driven insights. Deliver executive dashboards”

What You'll Achieve.

Improve productivity; Improve quality; Improve throughput; Improve customer satisfaction

Industry & Context.

Problems you'll solve

Analytical skills; Problem-solving skills; Interpret complex manufacturing data; Translate data into actionable insights

Eligibility Requirements

25% of the Time travel

What They're Looking For.

Must Have

Bachelor’s or Master’s Degree, 8 years of experience, analytical and problem-solving skills, design executive-level dashboards, statistics, business analytics, machine learning, and AI modeling, Python, R, or SQL proficiency, work independently and collaboratively, lead cross-functional work, operate under pressure, deliver rapid prototypes

Nice to Have

Experience in manufacturing operations, industrial engineering, or quality management, PMP or Scrum Master certification, managing large-scale, enterprise-level projects, Experience with cloud platforms, supporting operational intelligence, enterprise decision-support initiatives, aggregating analytics from shopfloor systems, MES, or operational workflows, Familiarity with Industry 4.0 technologies

What You'll Do.

Deliver data-driven insights

Deliver executive dashboards

Deliver scenario modeling

Predict operational risks

Improve proactive decision-making

Develop Control Tower analytics

Develop operational intelligence solutions

Design scalable dashboards

Develop decision-support tools

Develop AI-enabled workflows

Drive advanced analytics

Improve operational visibility

Improve KPI definitions

Improve metric reliability

Partner with manufacturing teams

Partner with engineering teams

Partner with quality teams

Partner with supply chain teams

Partner with digital teams

Lead rapid prototyping

How You'll Work.

Team & Collaboration

Cross-functional digital initiatives; Cross-functional work; Global environment

Communication Scope

Present technical information; Executive presentations

Process & Methodology

Program management discipline, Planning, Execution, Stakeholder management

Full Job Description

## **Job Description** As a Data Scientist for Global Manufacturing Analytics, you will combine analytics, statistics, machine learning, AI, and business understanding to solve complex manufacturing and operational challenges at scale. You will be part of the transformation team building end-to-end decision intelligence capabilities - from KPI design, data interpretation to operational insights, forecasting, scenario modeling, and business actions - to improve productivity, quality, throughput, and customer satisfaction across the global manufacturing network. You will lead cross-functional digital initiatives from concept to rollout- translating operational challenges into scalable decision-intelligence solutions, dashboards, models, and alerts that support both strategic and management decisions. **Responsibilities:** Deliver data-driven insights, executive dashboards, and scenario modeling to support manufacturing and operations decision-making. Apply statistics, machine learning, and AI techniques to identify patterns, predict operational risks, and improve proactive decision-making. Develop Control Tower analytics and operational intelligence solutions for areas such as: * productivity and throughput * quality and yield * delivery and backlog risk * cost and margin drivers * manufacturing network performance Design and develop scalable dashboards, decision-support tools, and AI-enabled workflows with strong focus on explainability, usability, and actionability. Drive automation and advanced analytics using Python, SQL, BI tools, and cloud technologies to improve operational visibility and reduce manual effort. Improve data quality, KPI definitions, and metric reliability to enable consistent and trusted decision-making across sites and regions. Partner with manufacturing, engineering, quality, supply chain, and digital teams to align analytics solutions with operational priorities and global standards. Lead rapid prototyping and MVP development to accelerate le

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