Data Analyst III

at  Thermo Fisher Scientific

JOB DESCRIPTION

Position Summary: The Data Analyst III role within the Analytical Instrument Group (AIG) will support the digital transformation across the AIG commercial finance organization. This role involves developing analytics, tools, and dashboards to empower business insights and improve decision-making for AIG commercial teams. The ideal candidate will possess deep technical skills, practical experience with large data sets, and superb communication and collaboration abilities to work effectively across teams. This highly visible role offers an early career talent the opportunity to gain a comprehensive understanding of data analytics, business intelligence, and commercial management.

MINIMUM REQUIREMENTS/QUALIFICATIONS:

• BS or MS Degree in Math, Statistics, Computer Science, Data Science, or a related field.
• 1-3 years of work experience in data analytics, digital enablement, or a related field.
• Excellent analytical and problem-solving skills, with experience in building data models.
• Proficiency in Excel, SQL, Python, R, and Power BI.
• Strong presentation skills and the ability to articulate complex data models and business problems.
• Ability to work across a matrix organizational structure and effectively influence business partners.
• Delf-motivated, able to drive actions to completion with intensity and ownership.
• Passionate about learning business and data analytics/science.
• Ability to travel (~10%).
  Benefits: We offer competitive salaries, an annual incentive bonus plan, 401K with company match up to 6%, tuition reimbursement, and a range of other employee benefits!

• Develop data analytics, models, and tools tailored to commercial needs to enhance insights and decision-making by collaborating with Division Commercial and Finance teams
• Create dashboards and reports to measure key trends and commercial performance, helping commercial leaders quickly diagnose funnel health and commercial execution, and providing insights for commercial and BU teams to assess opportunities and risks.
• Ensure data quality, accuracy, and readiness. Lead data clean-up, integration, transformation, and validation; collaborate with D&T and IT teams to build robust, efficient, and reliable data pipelines for various analytics needs.
• Build use cases and develop mock-ups. Lead user acceptance testing (UAT), demos, and provide regular training for tools and dashboards, and manage post-launch enhancements.
• Develop data analytics/science models to help commercial teams identify new leads, cross-selling opportunities, and market trend shifts.
• Experiment with predictive modeling to improve forecast accuracy, informing commercial strategy, resource deployment, and supply/demand planning.
• Proactively identify business problems and opportunities, translating business needs into quantitative analyses that uncover patterns and insights.
• Work with D&T and IT teams to deploy and improve data practices, enhancing data accessibility and quality, and fostering a culture of data-driven decision-making.
• Collaborate with Corporate Data Science and Commercial Analytics teams to adopt company innovations and established methodologies.