Data Quality Analyst

Location: Lagunilla, Costa Rica

Category: Operations

Employment Type: Full time

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Job Description

About Thermo Fisher Scientific Inc.

When you are part of the team at Thermo Fisher Scientific, you will have the opportunity to do meaningful work that makes a difference. Our company is the world leader in serving science, with annual revenue of more than $40 billion and approximately 120,000 colleagues globally. Join us in bringing our Mission to life every day: enabling 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.

Data Quality Analyst

As a Global Procurement Data Quality Analyst, you will play a critical role in enhancing the accuracy, consistency, and reliability of procurement data used for spend analytics, sourcing decisions, and procurement category reporting. This role combines data analysis, procurement process understanding, and stakeholder collaboration to identify data quality issues, support spend classification improvements and strengthen confidence in procurement data.

Job Responsibilities

• Conduct comprehensive assessments of master data and transactional data using procurement spend tools and analytics.
• Identify data quality issues, gaps, and inconsistencies through data profiling, validation, and analysis.
• Research, collect, analyze, and draw conclusions from procurement data.
• Review and evaluate supporting details, analyses, and business justifications for spend recategorization and classification improvement opportunities.
• Evaluate AI-enabled classification outputs, identify when additional business context or validation is needed, and provide structured feedback to improve classification accuracy and model performance.
• Execute data cleansing activities to resolve data quality issues, such as deduplication, categorization, standardization, and normalization.
• Collaborate with data owners, data providers, procurement category teams, and cross-functional stakeholders to resolve data issues and enrich procurement data.
• Communicate and present findings, recommendations, and data improvement opportunities to procurement category leaders and key stakeholders.
• Maintain clear documentation of data quality findings, actions, and decisions to support consistency, traceability, and audit readiness.
• Support continuous improvement initiatives related to data quality and spend classification.
• Perform special assignments and projects as required.

Minimum Requirements/Qualifications:

• Bachelor’s degree in Business Administration, Industrial Engineering, Data Analytics, Supply Chain, or a related field.
• 5+ years of work experience in buying, procurement, supplier quality, data management, process engineering, procurement analytics, or a similar role.
• Procurement domain knowledge in the context of spend analytics, supplier data, or category management is preferred.
• Experience with data analytics, reporting, and data preparation tools such as Excel, Power BI, SQL, Alteryx, AI-enabled tools, or similar platforms.
• General understanding of artificial intelligence and machine learning concepts, with the ability to deepen knowledge of AI/ML models and contribute to improvements in model logic and performance.
• Ability to interpret AI/ML-enabled classification model results and provide structured feedback to improve classification accuracy, process effectiveness, and data quality outcomes.
• Highly analytical, critical, and detail-oriented, with intellectual curiosity and the ability to question data, identify inconsistencies, and collaborate with stakeholders to improve data accuracy.
• High level of English language proficiency, both verbal and written.
• Strong communication and interpersonal skills to collaborate effectively with cross-functional teams, data providers, and procurement stakeholders.
• Strong time management, organizational, and change management skills.
• Project management skills with demonstrated ability to take initiative, track and manage own deadlines, and drive projects to completion.