Design, build, and maintain stakeholder-specific BI dashboards and analytical reports for procurement, sourcing, and warehouse KPIs
Define, develop, and evolve business-aligned KPIs supporting ML-driven products and procurement transformation initiatives
Perform exploratory and advanced data analysis to identify trends, root causes, and improvement opportunities
Identify and support resolution of data quality issues (ETL – Extract Transform Load) to ensure accurate, consistent, and reliable analytics
Analyze the datasets from different systems to develop Indirect Procurement Spend cube
Data Engineering & Data Lake Enablement
Extract, integrate, and transform data from Finance systems, Warehouse Management Systems (SAP EWM / WM and similar platforms) to provide insights for supplier negotiations.
Design and support scalable data pipelines using batch, CDC, API-based, and streaming ingestion mechanisms.
Ensure data reconciliation, validation, and standardization across inbound, outbound, inventory, and exception datasets.
Build and maintain feature-ready datasets in enterprise Dana data lakes to support analytics, ML, and AI models.
Enable near-real-time analytics for warehouse performance, sourcing activities, and supplier monitoring.
GenAI & LLMs for Sourcing Intelligence
Design and deploy Generative AI solutions (Gemini, Claude, OpenAI) to support:
Supplier discovery and evaluation
Creation of Taxonomy and Categorization
Sourcing strategy development
Market and category intelligence
Apply Large Language Models (LLMs) to analyze:
RFQs, RFPs, and tender documents
Supplier proposals and contracts
Market reports, pricing indices, and benchmarks
Automate generation of:
Supplier shortlists
Sourcing insights and risk summaries
Executive-ready sourcing recommendations
GCP Agentic AI & Market Intelligence Automation
Build Agentic AI systems that autonomously:
Scan public and paid data sources for supplier and category intelligence
Track supplier pricing, capacity, and global market movements
Monitor geopolitical, inflation, and logistics risk indicators
Continuously refresh market intelligence and trigger alerts for sourcing risks or opportunities
Collaboration & Delivery
Partner closely with procurement leaders, supply chain stakeholders, product owners, and IT/data engineering teams.
Translate business challenges into scalable analytics and AI solutions with measurable impact.
Support deployment, monitoring, and continuous improvement of ML and AI models.
Communicate insights through clear visualizations, reports, and executive presentations to facilitate decision-making at all levels of the organization.
requirements-expected :
Bachelor’s degree in computer science, Data Science, Information Technology, or a related field
5+ years of experience in data engineering, advanced analytics, or ML/AI roles
Strong experience with Excel, PowerPoint, SQL, and programming languages (ex: Java/Python, SAS, Polars, PySpark) and large-scale data processing tools
Hands-on experience with GenAI, LLM-based applications, prompt engineering, and AI agents
Experience working with SAP EWM / WM or similar ERP/WMS systems
Proficiency with MicroStrategy, Looker studio and Power BI tools
Experience with cloud platforms (GCP, Azure, BigQuery, Vertex AI) and modern Dana data lake architectures
Strong understanding of indirect procurement, sourcing, supplier management, and category intelligence
Execute analytical experiments to help solve problems across various domains like Retail, Wholesales, Warehouse, Marketing & Finance
Preferred Qualifications:
Experience across Indirect Procurement categories (IT, MRO, Facilities, Logistics, Professional Services)
Familiarity with warehouse and supply chain performance metrics
Exposure to MLOps, feature stores, and scalable AI deployment frameworks
offered :
Stable employment in an international corporation, which is constantly growing
Opportunities to expand expertise across data science, AI, procurement, and supply chain domains.
Private medical care and group insurance, also for family members
Cash benefits as part of the Social Benefits Fund, i.e., Christmas allowance
Co-financed sports card
Team and company integrations after hours
Hybrid work model
Workplace based in Warsaw, Poland
benefits :
sharing the costs of sports activities
private medical care
sharing the costs of foreign language classes
sharing the costs of professional training & courses
