Job Description

As the Global Manufacturing Data Scientist, you will develop and deploy analytics, automation, and predictive models that improve productivity, margin, quality, throughput, and customer satisfaction across the global manufacturing network.

You will lead cross-functional digital initiatives from concept to rollout—translating manufacturing challenges into scalable data products (dashboards, models, alerts) and ensuring solutions are implemented, adopted, and sustained through strong governance, program management, and change management.

Role and Responsibilities:

Provide data-driven insights, dashboards, and scenario modeling to support manufacturing leaders and factory operations teams in both day-to-day execution and strategic decision-making.

Build and maintain manufacturing KPI views covering productivity, cost/margin, quality, delivery, customer satisfaction, and operational health, with clear exception signals and root-cause pathways.

Develop “control tower”-style analytics to generate insights from data (capacity constraints, yield loss, quality risks, cycle time deviations, throughput gaps) to support management decision-making and operational focus.

Build and scale analytics solutions across key manufacturing domains, such as

• Throughput and productivity
• Yield, scrap, and quality analytics
• Cost and margin drivers (labor efficiency, material usage, rework impact)
• Delivery performance and customer impact
• Value chain and manufacturing network efficiency
• Operational scenario planning and simulations aligned with the digital roadmap

Design and develop dashboards and insight-generating tools for senior management, ensuring clarity, usability, and actionability.

Drive automation and advanced analytics using Python, SQL, and BI tools to scale insight generation and reduce manual reporting effort.

Drive continuous improvement in data quality, definitions, and metric reliability to ensure consistent decision-making across sites and regions.

Partner with manufacturing SMEs, engineering, quality, and digital stakeholders to align analytics with global standards, governance, and process maturity efforts.

Lead cross-functional programs to embed analytics into daily management systems, performance reviews, and continuous improvement routines.

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, 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.
• 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 Qualifications

• Experience in manufacturing operations, industrial engineering, or quality management.
• PMP or Scrum Master certification preferred, with proven experience managing large-scale, enterprise-level projects.
• Familiarity with Industry 4.0 technologies (IIoT, digital twins, automation systems).
• Experience with cloud platforms such as AWS, Azure, or Google Cloud.
• Knowledge or hands-on experience with Generative AI (GenAI), Large Language Models (LLMs), Agentic AI and AI-driven automation use cases.
• Experience embedding analytics into shopfloor systems, MES, or operational workflows.

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/locationsAgilent 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 Time

Shift:

Day

Duration:

No End Date

Job Function:

Administration