Procurement Data Science & Analytics Manager (2 years contract)
Mondelēz International · Singapore
About this role
The Procurement Data Science & Analytics Manager will combine hands-on analytical execution, data governance support, and operational enablement to improve data quality, generate actionable insights, and contribute to digital and analytics transformation initiatives within Procurement. Initially focused on the AMEA (Asia, Middle East & Africa) region, the role will evolve to support broader global Procurement analytics needs. Responsibilities include developing analytics and reports, leveraging tools like Sievo, analyzing complex datasets, applying statistical and machine learning techniques, and supporting automation. The role also involves implementing enterprise data governance standards, maintaining business definitions, and collaborating with cross-functional stakeholders to drive data-informed decision-making. Requirements include a Bachelor's degree in a relevant field, solid experience in data science or analytics, and proficiency in tools such as Power BI, Tableau, Alteryx, and SQL. Familiarity with governance tools like Ataccama or Collibra is highly valued. This is a 2-year fixed-term contract position based in Harbourfront, Singapore, with no relocation support provided.
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A focused preparation guide, built around this job’s responsibilities and requirements.
✦ AI-generated guide
Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.
01
Understand the role
What matters most
Regional Data Governance Implementation
The role requires immediate focus on establishing and adopting enterprise data governance standards within the AMEA region. This involves defining business rules, maintaining data catalogues, and ensuring data quality metrics are met to support regional procurement operations.
Procurement Analytics and Insight Delivery
You must develop and deliver actionable reports and analytics using tools like Sievo, Power BI, and Tableau. The priority is to translate complex procurement datasets into clear business recommendations that improve decision-making and operational performance.
Cross-Functional Stakeholder Enablement
Success depends on collaborating with Procurement, Finance, and Supply Chain teams to drive data-informed decisions. You are expected to provide training and support change management initiatives to ensure users effectively adopt new analytics tools and governance practices.
Digital Transformation and Automation
The position involves contributing to digital transformation by identifying and implementing advanced analytics use cases, predictive models, and automation workflows to simplify and optimize procurement reporting processes.
Likely challenges to think through
Navigating a Complex Matrixed Environment
Working across the AMEA region involves diverse markets and stakeholders. You may face difficulty aligning varying regional data needs with global enterprise standards. Prepare by demonstrating experience in managing stakeholder expectations in large, decentralized organizations.
Balancing Tactical Execution with Strategic Governance
The role requires a dual focus on hands-on analytical work and long-term governance maturity. You may struggle with competing priorities between immediate reporting requests and the slower, methodical process of defining data quality rules. Prepare by showcasing your ability to prioritize tasks based on business impact.
Managing Data Quality in Legacy Systems
Implementing governance standards often reveals underlying data inconsistencies. You will likely encounter resistance or technical hurdles when cleaning and standardizing complex procurement data. Prepare by highlighting your experience in data quality management and working with tools like Ataccama or Collibra.
03
Practice your answers
Technical practice
Data Governance Implementation
What to coverExplain how you would approach implementing enterprise data governance standards within a procurement function. Focus on your experience defining business definitions, establishing data quality rules, and managing data catalogues using tools like Collibra or Ataccama.
Procurement Analytics Workflow
What to coverDescribe a scenario where you used Alteryx or SQL to automate a complex procurement reporting process. Emphasize how you ensured data accuracy and how the automation improved operational efficiency for stakeholders.
Data Visualization for Decision Support
What to coverHow do you translate complex procurement datasets into actionable insights using Power BI or Tableau? Discuss your approach to designing dashboards that cater to both technical teams and non-technical business stakeholders.
Predictive Modeling in Supply Chain
What to coverProvide an example of a predictive model you developed to identify procurement trends or risks. Explain the statistical techniques used and how you validated the model's performance against actual business outcomes.
Data Quality Management
What to coverHow do you monitor and improve data quality in a large, matrixed organization? Suggestion: Discuss your methodology for identifying root causes of poor data quality and how you partner with data stewards to enforce validation processes.
Integration of Procurement Tools
What to coverHow would you approach integrating data from specialized procurement platforms like Sievo with broader enterprise data systems? Address the challenges of data mapping, consistency, and maintaining a single source of truth.
Statistical Analysis Application
What to coverDescribe how you have applied statistical analysis to optimize procurement performance. Focus on how you identified variables that influence cost or supply chain reliability and how you communicated these findings to drive change.
Data Modeling for Procurement
What to coverExplain your process for designing a data model that supports global procurement analytics. Suggestion: Address how you balance the need for standardized global metrics with the specific, localized requirements of regions like AMEA.
Behavioural practice
Cross-Functional Stakeholder Management
What to coverDescribe a time you had to align stakeholders from different functions, such as Finance and Supply Chain, on a new data initiative. How did you manage conflicting priorities and ensure the final solution met everyone's needs?
Driving User Adoption
What to coverTell me about a time you introduced a new analytics tool or governance process to a team that was resistant to change. What specific actions did you take to support training, enablement, and long-term adoption?
Navigating Complex Matrix Environments
What to coverGive an example of how you have successfully delivered a project in a fast-paced, global, matrixed organization. How did you coordinate with remote teams and external partners to ensure timely value delivery?
Translating Technical Findings
What to coverDescribe a situation where you had to present complex analytical findings to senior leadership. How did you simplify the information to ensure they could make an informed, data-driven decision?
02
Sharpen your knowledge
Topics to prepare
Procurement Data Governance Frameworks
Review the principles of enterprise data governance, specifically focusing on data quality rules, business glossaries, and data cataloging. Exercise: Draft a sample data quality rule for a procurement dataset (e.g., supplier categorization) and map it to a business definition. This is relevant because the role requires implementing governance standards and maintaining business definitions within the AMEA region.
Supply Chain and Procurement Analytics
Study common procurement KPIs such as spend analysis, supplier performance metrics, and risk identification. Exercise: Create a conceptual framework for analyzing procurement trends across multiple countries. This is relevant as the role involves generating actionable insights for the AMEA region and supporting global procurement needs.
Skills to revise
Data Visualization and BI (Power BI/Tableau)
Practice building interactive dashboards that translate complex datasets into clear business recommendations. Exercise: Design a mock dashboard layout that tracks procurement spend by category and region. This is relevant because the role requires developing reports and insights for cross-functional stakeholders.
Data Transformation with Alteryx
Focus on automating data preparation and blending workflows. Exercise: Build an Alteryx workflow that cleans and joins two disparate datasets (e.g., a supplier list and a transaction log). This is relevant as the role involves simplifying and automating analytics processes.
SQL for Data Analysis
Refine skills in writing complex queries to extract and aggregate data from large databases. Exercise: Write a SQL query to identify top-spending suppliers over a specific time period. This is relevant because the role requires analyzing large and complex datasets to identify trends and opportunities.
04
Your preparation checklist
Prepare a procurement-focused analytics project walkthrough
Develop a concise presentation of a past project where you used SQL and visualization tools (Power BI or Tableau) to solve a procurement or supply chain challenge. Focus on how you translated complex data into actionable business recommendations.
Map your experience to data governance frameworks
Prepare specific examples of how you have implemented data quality rules, maintained business glossaries, or used governance tools like Collibra or Ataccama. Be ready to discuss how you manage data definitions in a complex, matrixed environment.
Demonstrate technical proficiency in automation
Prepare to explain how you have used Alteryx or similar tools to automate reporting processes. Highlight a specific instance where you simplified a manual workflow to improve data accuracy or operational productivity.
Formulate questions on AMEA procurement priorities
Prepare thoughtful questions regarding the current state of procurement data maturity in the AMEA region and the specific business challenges you will be expected to address during the two-year contract period.
Refine your stakeholder engagement narrative
Prepare examples of how you have successfully collaborated with non-technical stakeholders in Finance or Supply Chain to drive adoption of new analytics tools or governance standards, emphasizing your approach to change management.
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