Description

You build and maintain internal tools and data pipelines that monitor supply chain risk and automate procurement workflows.

This role is hybrid.

Responsibilities

• Validate and cleanse BOM and MPN data, cross-referencing supplier data against external sources like Z2Data and DigiKey.
• Build automated data quality checks and exception workflows to identify lifecycle risks and single-sourced components.
• Develop Python-based internal tools, web dashboards, and APIs for supply chain risk monitoring.
• Integrate external market intelligence platforms into internal workflows and create AI-assisted features for risk scoring.
• Translate supply chain business problems into technical solutions, prototyping tools rapidly and automating manual processes.

Required Skills

• 5+ years in a technical analyst, solutions engineer, or applied data science role.
• Strong Python proficiency, including scripting, pandas for data manipulation, and API integrations.
• Proficient in SQL, capable of querying large datasets, writing complex joins, and working with partitioned tables.
• Experience connecting to and working with external APIs and data sources.
• Ability to build working internal tools quickly using web apps, dashboards, notebooks, or scripts.
• Comfortable handling messy, real-world data, including reconciling across sources and managing edge cases.
• Strong communication skills to present findings clearly to non-technical stakeholders.

Preferred Skills

• Background in supply chain, procurement, or hardware operations, with familiarity in electronic component data (BOMs, AVLs, MPNs).
• Experience with component databases such as DigiKey, Octopart, Z2Data, or SiliconExpert.
• Comfort with AI/ML tools, including LLMs, classification models, or using AI assistants to accelerate work.

Key Skills

Education

Bachelor's degree