Procurement Data Quality Analyst

at  Thermo Fisher Scientific

JOB DESCRIPTION

About Thermo Fisher Scientific Inc.
When you’re part of the team at Thermo Fisher Scientific, you’ll have the opportunity to do important work that makes a difference. Our company is a global leader in serving science, with a mission to enable our customers to make the world healthier, cleaner, and safer. We value the power of diverse talent, backgrounds, and experiences, and have built an inclusive and collaborative environment where everyone’s contributions are valued and respected.

MINIMUM REQUIREMENTS/QUALIFICATIONS:

• Bachelor’s degree in business administration, industrial engineering, IT, or related field.
• 5+ years of work experience in a buyer, supplier quality, data management, process engineering or similar role.
• General understanding of artificial intelligence, specifically machine learning.
• Expertise in data analytics tools (e.g., Excel, ERP, Power BI)
• Functional understanding of advanced data analytics tools (e.g., SQL, AI, Python, R)
• High level of English language proficiency (verbal and written).
• Strong communication & interpersonal skills to collaborate effectively with cross-functional teams, data providers, and category leaders
• Time & Change Management
• Highly analytical with proven attention to detail: will work closely with data providers and category leaders to achieve high data accuracy.
• Procurement domain knowledge in the context of spend analytics is a plus.
• Project management skills with demonstrated ability to take initiative, track and manage own deadlines, and drive projects to completion.
  Join us at Thermo Fisher Scientific, where you will have the opportunity to grow professionally and contribute to our ambitious goals. Apply today at http://jobs.thermofisher.com.

• Conduct comprehensive assessments of master data and transactional data using Procurement spend tools.
• Identify data quality issues, gaps, and inconsistencies through data profiling and data validation.
• Execute data cleansing activities to resolve data quality issues, such as deduplication, categorization, standardization, and normalization.
• Communicate & present recommendations to category leadership to drive improvements to spend classifications.
• Actively collaborate with data owners and stakeholders to enrich data, by leveraging data enrichment tools and conducting research.
• Evaluate all necessary details, analyses, and justifications for recategorization of spend data
• Research, collect, analyze, and draw conclusions from procurement data
• Perform special assignments and projects as required