Senior Business Data Analyst

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