Data Analyst - Supply Chain

Work Schedule

Standard (Mon-Fri)

Environmental Conditions

Office

Job Description

Job Description

At Thermo Fisher Scientific, you will help enable our customers to make the world healthier, cleaner and safer.

The Business Data Analyst will build foundational datasets, analytics and automation capabilities to support supply chain decisions across Asia Pacific countries. The role will turn enterprise data into reliable reporting, reusable data models and practical insights.

In the short term, the analyst will support integration projects, including process mapping and data and reporting integration. Over the medium to long term, the role will support multiple facets of the supply chain including Distribution, Logistics, Customer Service, Planning and Procurement, flexing across supply chain data requirements as priorities evolve.

Key Responsibilities

Build and maintain reusable foundational datasets, data models and Power BI semantic models. Use SQL and advanced Excel to extract, transform, profile, reconcile and validate data from multiple enterprise systems.

Develop Power BI dashboards, reports and scorecards for recurring and ad hoc needs. Create reusable DAX measures, KPIs and calculated columns, improving report accuracy, performance, scalability and usability.

Automate manual reporting, data preparation and repetitive analysis, using Python or similar tools where appropriate. Support discovery, implementation, testing and adoption.

Partner with supply chain, commercial, finance and technology teams to translate business questions into analytical requirements, meaningful KPIs and recommendations.

Provide short-term integration project support through process mapping, data mapping and validation, and data and reporting integration.

Support evolving data and analytics needs across supply chain functions, adapting datasets, reports and analysis to different operational priorities.

Analyze operational issues, validate assumptions and investigate gaps between system data and actual performance. Identify root causes and support agreed actions.

Document data sources, transformations, business rules, assumptions and metric definitions. Troubleshoot BI, data quality, performance and access issues with technology teams.

Identify process improvements and support simpler, standardized ways of working.

Use approved AI tools for reporting, summarization, quality checks and insight development, validating outputs against trusted data.

Contribute to BI standards, governance, documentation and training to improve reporting consistency and data literacy.

Manage multiple assignments and communicate findings, recommendations, progress and risks across global, cross-functional teams.

Qualifications and Skills

• •Bachelor's degree in Computer Science, Data Science, Business Analytics, Information Systems, Engineering, Mathematics, Statistics, Economics or a related quantitative discipline; equivalent relevant professional experience may be considered.
• •Typically 3+ years in data analytics, BI, reporting, analytics engineering, process improvement or a related discipline, preferably in supply chain, commercial operations, finance, technology or consulting.
• •Hands-on experience with Power BI or a similar BI platform, including dashboards, reporting, visualization and semantic or data modeling.
• •SQL skills, including joins, aggregations, subqueries, common table expressions, transformation, reconciliation and analytical querying.
• •Advanced Excel skills, including pivot tables, lookup and logical functions, validation, preparation and analysis of large or complex datasets.
• •Working knowledge of DAX, relational databases, reporting datasets, data structures and basic data modeling.
• •Ability to translate business questions and process needs into analytical requirements, KPIs, reports and recommendations.
• •Strong analytical and problem-solving skills, with attention to data quality, accuracy, detail and root causes.
• •Clear written and spoken English, with the ability to explain complex data to diverse audiences.
• •Ability to collaborate across functions, levels and geographies, manage competing priorities and work independently in a dynamic environment.
• •Preferred: experience in different aspects of the supply chain
• •Preferred: working knowledge of Python for data manipulation, validation, analysis or automation.
• •Beneficial: exposure to ETL/ELT, data integration, cloud data platforms, data warehouses, Power Platform, Databricks or similar technologies.
• •Beneficial: exposure to data governance, quality management, semantic modeling, metadata, generative AI or conversational analytics.

This description outlines the general responsibilities and qualifications of the role. Other duties may be assigned as needed.