Data Scientist (Global Manufacturing Analytics)
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 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/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.