Sr. Demand Planning Data Analyst

Position Overview

As a Sr. Demand Planning Data Analyst at Thermo Fisher Scientific, you will enhance inventory management and drive performance improvements through exceptional data analytics and reporting. You will lead multi-functional projects within the CCG Supply Chain, crafting visual analytics to provide insights and develop data-driven problem-solving and communication. Your role will involve handling demand variability, ensuring product availability, leading product lifecycle management, collaborating with teams, analyzing business needs, and maintaining data integrity.

Employment Type

• Full time

Work Schedule

• Standard (Mon-Fri)

Environmental Conditions

• Office

Responsibilities

• Product Lifecycle Management: Lead product lifecycle management, including portfolio expansion, new item setup, product conversion, rationalization/discontinuation, and inventory optimization.
• Demand Planning: Apply proactive demand sensing techniques, adjust based on business intelligence, and address anomalies.
• Performance Metrics: Own department metrics like Customer Fill-rate, Days of Supply, Inventory Dollars, and Financial Performance by analyzing data.
• Collaboration & Improvement: Support collaboration with portfolio management, purchasing, key suppliers, and the category planning team; lead continuous improvement projects.
• Data Visualization & Reporting:
  • Build and maintain dashboards and reports using Power Apps, Power BI, Tableau, and Excel.
  • Analyze business needs to build detailed reporting specifications; integrate data for comprehensive reporting tools.
  • Maintain data accuracy and integrity in reports; work with collaborators to meet their reporting needs; improve current reports for performance and usability.
• Data Analysis & Insights:
  • Analyze large datasets, extract meaningful insights, and contribute to data-driven decision-making processes.
  • Collaborate with multi-functional teams to understand instrument behavior and application impact, applying statistical, mathematical, and machine learning techniques to identify root causes.
  • Apply sophisticated statistical models and data algorithms to identify correlation of parameters and data changes to automated processes, developing key actions to improve our applications.
  • Apply statistical methods and machine learning algorithms to develop predictive models and actionable insights.
• Solution Design: Act as a data driver in solution design, proposing data and parameters for collection by engineering teams. Find and design appropriate solutions for data visualizations for different use cases (PowerApps, Power BI).
• Communication & Training:
  • Interpret and communicate findings to both technical and non-technical team members through reports and presentations.
  • Brainstorm new improvements to streamline current techniques.
  • Train end-users on Power BI tools and stay informed on the latest data visualization trends.

Key Proficiencies

• Proven capability in sophisticated data analytics and strong presentation skills to influence senior-level outcomes.
• Effective written and oral communication skills.
• Self-motivated with a strong bias for action.
• Dedication to continuous learning and development.

Required Experience

• Education: Requires a Bachelor’s Degree, preferably in Supply Chain Management, Operations Management, Business, or a similar field.
• Certifications: APICS certification preferred.
• Professional Experience: 5+ years of experience in Supply Chain Management, Inventory Management, Warehouse/Logistics, SIOP, or a similar field.
• Data Visualization Tools: Minimum of 3 years of demonstrable experience with data visualization tools, especially Power BI, Power Apps, and Excel.

Skills That Will Make It Easier

• Ability to work in a multi-functional team and readiness to offer help.
• Proficient in the English language.
• Competent oral and written communication skills.
• Bachelor’s degree in computer science, data analytics, or a related field emphasizing data-driven analysis and decision-making, or equivalent experience.
• Proficient in Python with knowledge of data science libraries.
• Advanced knowledge of sophisticated data analytics, methodologies, and predictive data models.
• Experience with SQL and Cognos databases.
• Experience with data visualization tools.