Data Scientist (Global Manufacturing Analytics)

Reposted 9 Days Ago
Be an Early Applicant
Penang, Daerah Timor Laut, Penang, MYS
In-Office
300K-400K Annually
Senior level
Biotech
The Role
Develop and deploy models to improve manufacturing productivity. Lead analytics initiatives, create dashboards, and ensure data quality for operational insights.
Summary Generated by Built In
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 learning, validate concepts, and scale business impact.

Qualifications

Bachelor’s or Master’s Degree in Data Science, Statistics, Computer Science, Engineering, or a related field.

At least 8 years of experience in data science, manufacturing analytics, or equivalent work experience.

Strong analytical and problem-solving skills with the ability to interpret complex manufacturing data and translate it into actionable insights.

Proven experience in designing executive-level dashboards and insight-driven decision tools.

Strong knowledge and hands-on experience in statistics, business analytics, machine learning, and AI modeling, with practical application in manufacturing or operations.

Excellent communication skills, both written and verbal, with the ability to present technical information to non-technical stakeholders and senior leaders.

Experience in development and maintaining data visualization tools such as Tableau, Power BI, Qlik, Spotfire, or similar, for enterprise-wide users.

Proficiency in programming languages such as Python, R, or SQL.

Ability to work independently and collaboratively in a fast-paced, global environment.

Demonstrated ability to lead cross-functional work with strong program/project management discipline (planning, execution, stakeholder management).

Ability to operate under pressure and deliver rapid prototypes (MVPs) to validate concepts, de-risk assumptions, and confirm direction in fast-paced environments.

Preferred qualification

Experience in manufacturing operations, industrial engineering, or quality management.

PMP or Scrum Master certification preferred, with proven experience managing large-scale, enterprise-level projects.

Experience with cloud platforms such as AWS, Azure, or Google Cloud.

Experience supporting operational intelligence, or enterprise decision-support initiatives.

Experience with aggregating analytics from shopfloor systems, MES, or operational workflows.

Familiarity with Industry 4.0 technologies (IIoT, digital twins, automation systems).

Additional Details

This job has a full time weekly schedule.

Our pay ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. During the hiring process, a recruiter can share more about the specific pay range for a preferred location. Pay and benefit information by country are available at: https://careers.agilent.com/locations

Agilent Technologies Inc. is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability or any other protected categories under all applicable laws.Travel Required: 25% of the TimeShift: DayDuration: No End DateJob Function: Administration

Skills Required

  • Bachelor's or Master's Degree in Data Science, Statistics, Computer Science, Engineering, or related field
  • At least 8 years of experience in data science or manufacturing analytics
  • Strong analytical and problem-solving skills
  • Proven experience in designing executive-level dashboards
  • Strong knowledge in statistics, machine learning, and AI modeling
  • Excellent communication skills
  • Experience with data visualization tools
  • Proficiency in programming languages such as Python, R, or SQL
  • Ability to work independently and collaboratively
  • Demonstrated ability to lead cross-functional work

Agilent Technologies Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Agilent Technologies and has not been reviewed or approved by Agilent Technologies.

  • Retirement Support The core U.S. package highlights a generous 401(k) match as a strength. Retirement programs are positioned as competitive within the company’s total rewards.
  • Equity Value & Accessibility An Employee Stock Purchase Plan at a discount provides accessible equity and augments total compensation. Ownership opportunities are presented as a notable advantage alongside retirement benefits.
  • Leave & Time Off Breadth Flexible Time Off, company holidays, a personal holiday, and paid volunteer time create a broad leave offering. Time off can accrue into multiple weeks in the first year, supporting flexibility.

Agilent Technologies Insights

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The Company
HQ: Santa Clara, CA
17,369 Employees
Year Founded: 1999

What We Do

Analytical scientists and clinical researchers worldwide rely on Agilent to help fulfill their most complex laboratory demands. Our instruments, software, services and consumables address the full range of scientific and laboratory management needs—so our customers can do what they do best: improve the world around us. Whether a laboratory is engaged in environmental testing, academic research, medical diagnostics, pharmaceuticals, petrochemicals or food testing, Agilent provides laboratory solutions to meet their full spectrum of needs. We work closely with customers to help address global trends that impact human health and the environment, and to anticipate future scientific needs. Our solutions improve the efficiency of the entire laboratory, from sample prep to data interpretation and management. Customers trust Agilent for solutions that enable insights...for a better world.

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