New opportunity

Intern, GOBM pricing & BOS & PRPO

STMicroelectronics · Singapore

About this role

The Role: You will develop AI-enabled solutions and digital automation tools to improve pricing validation, BOS management, SAP data accuracy, PRPO processing efficiency, and GRN compliance in GOBM. This internship provides hands-on exposure to SAP-related business processes, procurement operations, data analytics, artificial intelligence, and workflow automation. Projects: 1. Leverage AI to validate new-device prices against MQ/MPI/BOS by identifying pricing discrepancies, missing information, and setup errors. 2. Develop an automated tool for BOS-SAP price reconciliation to detect inconsistencies and missing codes. 3. Create AI-enabled workflows to automate non-production PRPO activities and validate supplier documentation for GRN triggering. Requirements: Currently pursuing a degree in Computer Science, Information Technology, Data Science, Information Systems, Software Engineering, or Business Analytics. Basic programming knowledge in Python, SQL, or other scripting languages. Proficiency with Microsoft Access, Power BI, Power Automate, and Excel. Familiarity with Data Analytics and Generative AI applications. Strong analytical, problem-solving, and communication skills. Ability to handle large datasets. Knowledge of SAP or ERP systems is considered a plus. Benefits: Practical exposure to SAP and procurement processes, experience in AI and automation, and the opportunity to work on real business challenges and process improvement initiatives.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

PythonSQLMicrosoft AccessMicrosoft Power BIPower AutomateExcelData AnalyticsGenerative AISAPERP systemsAnalytical skillsProblem-solvingData processing

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Get interview-ready for this role

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

  • Automation of Procurement Workflows

    The primary objective is to develop AI-enabled solutions to streamline non-production PRPO activities and GRN compliance. You will be expected to translate manual procurement tasks into automated workflows using tools like Power Automate to improve overall process efficiency.

  • Data Accuracy and Reconciliation

    A core priority is ensuring the integrity of SAP data by performing regular reconciliations between BOS and SAP systems. You must be able to identify pricing discrepancies, missing material codes, and setup errors within large datasets to maintain financial and operational accuracy.

  • AI-Driven Pricing Validation

    You will leverage AI to validate new-device prices against internal benchmarks like MQ, MPI, and BOS. This requires applying data analytics skills to compare complex pricing structures and identify inconsistencies that could impact procurement operations.

Likely challenges to think through

  • Navigating Complex ERP Environments

    While SAP knowledge is a plus, you will likely face a steep learning curve regarding the specific procurement and pricing modules used by STMicroelectronics. Prepare by reviewing general ERP data structures and understanding how procurement data flows from purchase requests to goods receipt.

  • Managing Large and Unstructured Datasets

    The role involves handling large volumes of pricing and procurement data which may contain inconsistencies. Prepare by demonstrating your ability to clean, structure, and analyze data using Python or SQL, and be ready to explain how you handle missing or erroneous information in a real-world business context.

  • Bridging Technical Solutions with Business Needs

    You must translate technical AI and automation capabilities into practical improvements for the GOBM team. Prepare by practicing how to explain your technical approach to non-technical stakeholders, ensuring your automated tools actually solve the specific pain points of the procurement team.

03

Practice your answers

Technical practice

Data Reconciliation Logic

What to coverExplain how you would approach reconciling two large datasets, such as BOS and SAP pricing, to identify discrepancies. Focus on your methodology for handling missing keys, data type mismatches, and the logic used to flag anomalies.

Automation with Power Automate

What to coverDescribe a scenario where you would use Power Automate to streamline a manual procurement task. Discuss how you would handle error logging and ensure the workflow remains robust when processing variable supplier documentation.

SQL for Data Analysis

What to coverHow would you use SQL to extract and clean data from a large ERP database for analysis? Mention specific clauses or functions you would use to join tables and filter for specific pricing errors.

Generative AI in Workflow Automation

What to coverHow can Generative AI be applied to validate unstructured supplier documents like emails or invoices? Discuss the trade-offs between using pre-trained models versus fine-tuning for specific document extraction tasks.

Data Visualization for Stakeholders

What to coverWhen building a Power BI dashboard for pricing validation, what key performance indicators (KPIs) would you prioritize to help management track process efficiency? Explain how you ensure the data remains accurate and up-to-date.

Python for Data Processing

What to coverDescribe how you would use Python libraries like Pandas to handle large datasets that exceed Excel's capacity. Focus on techniques for data cleaning, transformation, and merging multiple sources.

ERP System Fundamentals

What to coverIf you have experience with SAP or similar ERP systems, explain how data integrity is maintained across different modules. If you lack direct experience, describe how you would research and map data fields between two disparate systems.

Handling Data Inconsistencies

What to coverWhat steps do you take when you identify a recurring data inconsistency in a production environment? Explain your process for root cause analysis and how you would propose a long-term automated fix.

Behavioural practice

Managing Complex Projects

What to coverDescribe a time you had to manage multiple project tasks simultaneously. How did you prioritize your work to ensure all deadlines were met while maintaining high quality?

Stakeholder Communication

What to coverTell me about a time you had to explain a technical finding or a data-driven insight to a non-technical stakeholder. How did you ensure they understood the impact and the recommended action?

Problem-Solving Under Pressure

What to coverGive an example of a time you encountered an unexpected obstacle while working on a data project. What was your immediate action, and how did you resolve the issue?

Continuous Improvement Mindset

What to coverDescribe a situation where you identified a manual process that could be improved. What steps did you take to propose or implement an automated solution?

02

Sharpen your knowledge

Topics to prepare

  • Procurement and ERP Data Lifecycle

    Understand the flow of procurement data from Bill of Services (BOS) and Purchase Requisition/Purchase Order (PRPO) to Goods Receipt Note (GRN) triggering. Research how ERP systems like SAP manage these stages to ensure data accuracy and compliance. This is relevant as the role involves automating these specific business processes.

  • AI-Driven Data Validation and Reconciliation

    Study conceptual frameworks for using AI to detect anomalies in large datasets, such as comparing pricing across multiple sources (MQ/MPI/BOS). Practice identifying common data quality issues like missing codes or inconsistent formatting. This is directly applicable to the project of automating BOS-SAP price reconciliation.

Skills to revise

  • Workflow Automation with Power Automate

    Build a sample flow that triggers an action based on an email or document input, simulating the validation of supplier documentation. This prepares you for the requirement to create AI-enabled workflows for PRPO processing.

  • Data Analysis with SQL and Python

    Practice writing SQL queries to join tables and identify discrepancies between two datasets. Use Python libraries like Pandas to clean and validate large CSV files. This is essential for handling the large datasets mentioned in the job description.

  • Dashboarding with Power BI

    Create a dashboard that visualizes data inconsistencies or process efficiency metrics. Focus on clear reporting of 'corrective action tracking' as requested in the project description.

04

Your preparation checklist

  • Analyze the procurement-to-payment lifecycle

    Research the standard SAP procurement cycle, specifically focusing on Purchase Requisitions (PR), Purchase Orders (PO), and Goods Receipt Note (GRN) processes. Understanding how these documents link in an ERP system will help you discuss the automation projects mentioned in the job description.

  • Prepare a data reconciliation project walkthrough

    Create a small project or case study demonstrating your ability to reconcile two disparate datasets. Use Python or SQL to identify discrepancies between two tables, similar to the BOS-SAP price reconciliation task. Be ready to explain your logic for handling missing codes or data inconsistencies.

  • Demonstrate automation and dashboarding proficiency

    Prepare a portfolio piece using Power BI to visualize a dataset and Power Automate to trigger a simple workflow. This provides concrete evidence of your ability to build the digital tools required to improve process efficiency and reporting.

  • Formulate questions on AI implementation in GOBM

    Prepare thoughtful questions for the interviewers, such as: 'What are the primary data quality challenges currently faced in the GOBM pricing validation process?' or 'How does the team currently balance Generative AI outputs with the need for high accuracy in SAP data?'

  • Review Generative AI application in business workflows

    Be prepared to discuss how you would use Generative AI to validate supplier documentation or unstructured data. Research how LLMs can be integrated into existing workflows to reduce manual effort, specifically for document verification tasks.

AI-generated from the job information · Prepared Oct 27, 2026 (UTC)Useful preparation, not a guarantee of eligibility or an offer.

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