The Data & Analytics team within Global Indirect Procurement is a high-performance, high-integrity, and high-growth organization looking for motivated and talented individuals with a passion for data, new technology, and finding solutions to tough problems. Our vision is to transform procurement performance by applying analytics to make data-driven decisions that enhance business value, based on forward-looking, accurate, and reliable intelligence. Team members will help operationalize data and make it actionable, turning insight into action. Key Responsibilities: 1. Data Mining & Predictive Analytics:
Analyze large datasets related to indirect procurement invoice spend, purchase orders, suppliers, contracts, and market indices to identify patterns, correlations, and insights.
Develop and apply statistical models and algorithms (e.g., regression, clustering, time-series forecasting) to interpret complex data and support decision-making with valuable insights and trends.
2. Data Governance Support and Project Management:
Contribute to the organization's data governance strategy by supporting new technology implementations, ensuring the accuracy, consistency, and integrity of indirect procurement data.
Collaborate with data stewards and IT teams to maintain and improve data governance practices.
Lead and/or collaborate in cross-functional projects with diverse teams, providing data-driven support and ensuring alignment with business objectives, delivering high-quality results on time and within budget.
3. Insight-Driven Analytics:
Prioritize creative and innovative problem-solving that aligns with and fuels business strategy, focusing on forward-thinking, actionable outcomes rather than just retrospective reporting.
4. Process Improvement and Data Pipelines & Automation:
Identify opportunities for improving data management processes and implementing best practices.
Utilize advanced data analysis tools and technologies (e.g., SQL, Python, R, Tableau, Power BI) to extract, manipulate, and visualize data.
Focus on automating the end-to-end analytics pipeline, optimizing the flow of data from ingestion to insight generation. Design tools to accelerate time-to-insight by processing and analyzing data.
5. Storytelling with Data:
Convey complex information into compelling narratives, developing and presenting well-structured, clear, and concise presentations that highlight insights and recommendations grounded in data.
6. Collaboration and Support:
Work closely with Category, Strategy, Planning, Value, Compliance, and other GIP functions to understand their data needs and provide analytical support.
Provide guidance and mentorship to junior data analysts, fostering a collaborative and growth-oriented environment.
Foster a data-driven culture within Global Indirect Procurement, integrating business acumen with deep analytical insights.
7. Compliance and Best Practices:
Ensure compliance with data privacy regulations and industry standards.
Stay updated on emerging trends and technologies in data analysis and data management.
Education & Experience Recommended
A bachelor's degree in data science, Statistics, Computer Science, Business Analytics, or a related field is required.
A master's degree in a relevant field (e.g., MBA with a focus on analytics, MS in Data Science or Business Analytics) is preferred and can be advantageous for advanced roles.
Proficiency in English
At least 5-7 years of experience in data analysis, preferably within Procurement /Supply Chain or a related field.
Proven experience working with large datasets and complex data analysis tools.
Industry Knowledge: Experience in a relevant industry (e.g., manufacturing, technology) can be beneficial
Preferred Certifications
Certified Analytics Professional (CAP): Preferred to validate advanced analytical skills and expertise.
Microsoft Certified: Data Analyst Associate: Preferred to demonstrate proficiency with data visualization tools.
SQL Certification: Preferred to validate expertise in SQL for data querying and manipulation.
Knowledge & Skills 1. Data Visualization: Expertise in creating dashboards and reports using tools such as Power BI or Tableau, from identifying customer needs to production and maintenance. 2. Data Engineering: Proficiency in ETL processes (Extract, Transform, Load) and data warehousing methodologies. Skilled in developing and writing SQL queries and Python scripts to retrieve data from APIs. 3. Data Analysis Tools: Advanced proficiency in MS Excel, Power Query, and SQL, with experience performing advanced analytics combining multiple sources and purposes. 4. Automation: Experience with VBA Macros, Microsoft SharePoint, Microsoft Flow, Power Apps, and UiPath for process and reporting automation. 5. Advanced Analytics: Proficiency in Python or other statistical tools, with experience delivering solutions using techniques such as classification, regression, clustering, and time-series forecasting. 6. Communication and Influencing Skills: Excellent verbal and written communication skills to convey findings and recommendations effectively to stakeholders. Proven relationship management skills. Disclaimer
This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management.
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