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Thermo Fisher

Supply Chain Specialist II

Thermo Fisher · Lagunilla, Costa Rica

Full-timeOn-sitePosted 18 September 2026
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Job description

Work Schedule Standard (Mon-Fri) Environmental Conditions Office Job Description Job Description As part of the Thermo Fisher Scientific team, you’ll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner and safer. We provide our global teams with the resources needed to achieve individual career goals while helping to take science a step beyond by developing solutions for some of the world’s toughest challenges, like protecting the environment, making sure our food is safe or helping find cures for cancer. Summary The Supply Chain Specialist will support the Corporate Supply Chain team by analyzing operational, supplier, planning, procurement, and inventory data to identify trends, improve visibility, and support business decision-making. This role partners with Inventory Management, Planning, Supplier Management and Operations teams to develop and maintain reports, dashboards, data models, and analytical solutions that improve supply chain performance and operational efficiency. The analyst will support recurring and ad hoc analytics, investigate business performance drivers, automate reporting processes, improve data quality and accessibility, and contribute to the development of scalable self-service analytics capabilities. Key Responsibilities Develop, maintain, and enhance Power BI dashboards and recurring supply chain reports. Analyze supply chain data to identify trends, risks, performance gaps, and improvement opportunities. Support analytics related to supplier performance, inventory, planning, procurement, material availability, and operational performance. Write and maintain SQL queries to extract, combine, validate, and analyze data from multiple source systems. Build and maintain data models, calculations, KPIs, and reporting logic in Power BI. Perform data validation and root cause analysis to identify discrepancies and improve reporting accuracy. Partner with business stakeholders to understand reporting requirements and translate business questions into analytical solutions. Support automation of manual reporting and data preparation processes using available analytics and digital tools. Create clear visualizations and communicate analytical findings to technical and non-technical stakeholders. Document reporting logic, data definitions, processes, and analytical methodologies. Contribute to continuous improvement, standardization, and self-service analytics initiatives across the Supply Chain organization. Support the adoption of emerging analytics, automation, and AI-enabled tools where appropriate. Required Qualifications Bachelor's degree in Industrial Engineering, Business Analytics, Information Systems, Operations Management, Data Science, Engineering, or a related field. 3+ years of experience in supply chain analytics, operations analytics, procurement analytics, business intelligence, data analytics, or related functions. Strong SQL skills, including querying, joins, aggregations, and data transformation. Strong Power BI experience, including dashboard development, Power Query, DAX, and data modeling. Experience analyzing and interpreting datasets from multiple sources. Strong analytical and problem-solving skills. Ability to communicate analytical findings clearly to business stakeholders. Ability to manage multiple priorities and work effectively in a cross-functional environment. Preferred Qualifications Experience working with supply chain, planning, procurement, supplier management, inventory, or manufacturing data. Experience with Power Platform, Python, Excel automation, or related analytics tools. Familiarity with ERP, planning, procurement, or manufacturing systems. Experience developing automated or self-service reporting solutions. Exposure to forecasting, inventory optimization, supplier performance, or manufacturing operations. Exposure to AI-enabled analytics or productivity tools. CSCP, CPIM, Lean Six Sigma, Power BI, or Data Analytics certifications.

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