Description

Data Validation & Analysis

• Validate and cleanse internal BOM (Bill of Materials) and MPN (Manufacturer Part Number) data across systems
• Cross-reference supplier data against external sources (Z2Data, DigiKey, SiliconExpert) to identify gaps, risks, and inconsistencies
• Build automated data quality checks and exception workflows
• Deliver ad-hoc analyses, e.g., "which components in this program have lifecycle risk?" or "where are we single-sourced on long-lead parts?"

Internal Tools & Applications

• Build and iterate on custom internal tools for supply chain risk monitoring (Python, web-based dashboards, APIs)
• Integrate external market intelligence platforms into internal workflows
• Develop AI-assisted features - risk scoring, lifecycle classification, early warning signals
• Create self-service analytics and visualizations for non-technical sourcing leads

Solution Design

• Translate supply chain business problems into technical solutions
• Prototype fast - get a working tool in front of users within days, not months
• Work with existing data infrastructure (pipelines, tables, etc) rather than building from scratch
• Identify opportunities to automate manual processes with AI/LLM tools

Required Skills

• 5+ years in a technical analyst, solutions engineer, or applied data science role
• Strong Python - scripting, data manipulation (pandas), API integrations, light web development
• Proficient in SQL — can query large datasets, write complex joins, work with partitioned tables
• Experience connecting to and working with external APIs and data sources
• Ability to build working internal tools quickly - web apps, dashboards, notebooks, scripts
• Comfortable working with messy, real-world data - reconciling across sources, handling edge cases
• Strong communication — can present findings to non-technical stakeholders clearly

Nice to Have

• Supply chain, procurement, or hardware operations background
• Familiarity with electronic component data (BOMs, AVLs, MPNs, lifecycle stages)
• Experience with component databases (DigiKey, Octopart, Z2Data, SiliconExpert)
• Comfort with AI/ML tools - LLMs, classification models, or using AI assistants to accelerate work
• Web frameworks (Flask, Streamlit, React) for rapid prototyping
• Meta internal tools (Bento, Presto/Hive, Unidash, Dataswarm) or equivalent at scale

Key Skills

Education

Bachelor's degree