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.
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