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Data Intelligence Manager

Thermo Fisher Scientific

Data Intelligence Manager

full-timePosted: Aug 2, 2026Updated: Sep 1, 2026China, Shanghai

Job Description

Work ScheduleStandard (Mon-Fri)Environmental ConditionsOfficeJob DescriptionKey Responsibilities1. Data Intelligence Enablement & FrameworkOptimize and continuously enhance the commercial data intelligence framework and roadmap in line with business priorities.Standardize data definitions, business logic, KPIs, reporting standards, and dashboard architecture to ensure consistency and reliability.Build scalable reporting structures and reusable data products by leveraging enterprise systems and data capabilities, reducing duplication and manual effort.Partner with Commercial teams and Commercial Excellence Business Partners to translate priority business needs into data models, dashboards, metrics, and actionable insights.2. System, Data and Reporting IntegrationIntegrate data across DB and SFDC to streamline data logic and reporting workflows, improving system efficiency and data accessibility.Enhance data accuracy, consistency, and usability across reports and dashboards.Document data logic, reporting methodologies, refresh processes, and governance standards to support scalability and long-term sustainability.3. Dashboard, BI and Tech-report DevelopmentDesign, develop, and maintain Power BI dashboards and commercial analytics and intelligence solutions.Build customer-, product-, channel-, and sales-team-level dashboards to support data-driven decision-making.Enhance dashboard usability, automation, and self-service capabilities to improve adoption and efficiency.4. AI-enabled Analytics and AutomationExplore and apply AI-enabled analytics to improve reporting efficiency, business insight generation, and risk/opportunity identificationSupport automation of recurring reports, data cleansing, data tracking, and insight generationPartner with IT, digital, and DSC teams where needed to evaluate scalable AI/data solutionsImprove the efficiency of data preparation, reporting, and analytical workflowsKey Success MeasuresImproved consistency, accuracy, and reliability of commercial data and reporting.Reduced manual reporting effort and duplicated analysis.Increased adoption of standardized dashboards and reporting frameworks.Stronger analytical support for Commercial leaders and CE Business Partners.Improved data-driven decision-making in commercial planning and execution.Required Experience and Capabilities5-10 years of relevant experience in SAP ERP, data analytics, commercial analytics, business intelligence, or life sciences business environmentsSolid working knowledge of Power BI, Excel, SQL, data visualization, and automation/data transformation tools such as Python, Databricks, Power Query, or Power AutomateGood understanding of data governance, data quality management, and reporting standardizationFamiliarity with AI-enabled analytics, predictive analytics, or automated insight generation is a plusExperience collaborating with cross-functional teams such as Operations, Finance, Supply Chain, and CommercialEffective communication skills, with the ability to explain data logic and insights to both technical and business stakeholdersProactive and with a problem-solving mindset and the ability to manage multiple priorities

Locations

  • China, Shanghai

Skills Required

  • SAP ERPintermediate
  • Power BIintermediate
  • AI-enabled analyticsintermediate

Required Qualifications

  • 5-10 years of relevant experience in SAP ERP, data analytics, commercial analytics, business intelligence, or life sciences business environments (experience, 10 years)
  • Solid working knowledge of Power BI, Excel, SQL, data visualization, and automation/data transformation tools such as Python, Databricks, Power Query, or Power Automate (experience)
  • Good understanding of data governance, data quality management, and reporting standardization (experience)
  • Familiarity with AI-enabled analytics, predictive analytics, or automated insight generation is a plus (experience)
  • Experience collaborating with cross-functional teams such as Operations, Finance, Supply Chain, and Commercial (experience)
  • Effective communication skills, with the ability to explain data logic and insights to both technical and business stakeholders (experience)
  • Proactive and with a problem-solving mindset and the ability to manage multiple priorities (experience)

Responsibilities

  • 1. Data Intelligence Enablement & Framework
  • Optimize and continuously enhance the commercial data intelligence framework and roadmap in line with business priorities.
  • Standardize data definitions, business logic, KPIs, reporting standards, and dashboard architecture to ensure consistency and reliability.
  • Build scalable reporting structures and reusable data products by leveraging enterprise systems and data capabilities, reducing duplication and manual effort.
  • Partner with Commercial teams and Commercial Excellence Business Partners to translate priority business needs into data models, dashboards, metrics, and actionable insights.
  • 2. System, Data and Reporting Integration
  • Integrate data across DB and SFDC to streamline data logic and reporting workflows, improving system efficiency and data accessibility.
  • Enhance data accuracy, consistency, and usability across reports and dashboards.
  • Document data logic, reporting methodologies, refresh processes, and governance standards to support scalability and long-term sustainability.
  • 3. Dashboard, BI and Tech-report Development
  • Design, develop, and maintain Power BI dashboards and commercial analytics and intelligence solutions.
  • Build customer-, product-, channel-, and sales-team-level dashboards to support data-driven decision-making.
  • Enhance dashboard usability, automation, and self-service capabilities to improve adoption and efficiency.
  • 4. AI-enabled Analytics and Automation
  • Explore and apply AI-enabled analytics to improve reporting efficiency, business insight generation, and risk/opportunity identification
  • Support automation of recurring reports, data cleansing, data tracking, and insight generation
  • Partner with IT, digital, and DSC teams where needed to evaluate scalable AI/data solutions
  • Improve the efficiency of data preparation, reporting, and analytical workflows

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