The Randstad companies are responsible for finding talent to provide services for Philips. If you are selected to provide services to Philips, you will be employed by Randstad and will not be an employee of Philips.

Philips

Manufacturing Cost Engineers

Posted May 11, 2026
Project ID: PHIAJP00003838
Location
Colorado Springs
Hours/week
40 hrs/week
Timeline
1 year
Starts: May 15, 2026
Ends: May 14, 2027
Payrate range
55 - 58 $/hr
Application Deadline: May 15, 2026 12:00 AM

Job Responsibilities

  • Analyze and mine large datasets to identify trends, patterns, and business opportunities.

  • Design and develop dashboards, reports, and self-service tools for stakeholders.

  • Translate business requirements into data models and visual solutions.

  • Partner with cross-functional teams to understand data needs and deliver actionable insights.

  • Automate data extraction, transformation, and reporting processes.

  • Ensure data accuracy, integrity, and consistency across all outputs.

  • Communicate findings clearly through visualizations and presentations. 


Requirements:

Education

  • Bachelor’s degree in Data Analytics, Finance, Statistics, Computer Science, or a related field.

Experience

  • 1–3 years of experience in data analysis or a related role (internships included).

  • Proficiency in data visualization tools such as Tableau, Power BI, or similar platforms.

  • Strong skills in SQL and Excel; experience with Python or R is a plus.

  • Experience working with large datasets and relational databases.

  • Strong analytical thinking and problem-solving abilities.

  • Ability to communicate technical concepts effectively to non-technical stakeholders. 


Preferred Skills:

  • Manufacturing Principles

  • Master Data Management (MDM)

  • Business Acumen

  • Cost Optimization

  • Material Cost Management

  • Financial Planning & Analysis (FP&A)

  • Data Analysis & Interpretation

  • Cost Estimation

Additional Information:

  • Focused on automation of cost data processes to drive cost savings and operational efficiency.

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