People Operations and Data Analyst

WEKA

About The Position

WEKA is transforming how organizations build, run, and scale AI and accelerated compute workflows with NeuralMesh™, our intelligent, adaptive mesh storage system. Unlike traditional data infrastructures, which become more fragile as compute environments grow and performance demands increase, NeuralMesh becomes faster, stronger, and more efficient as it scales, providing a flexible, adaptable foundation for enterprise and agentic AI innovation that maximizes GPU utilization, accelerates time to first token, and lowers the cost of innovation. WEKA is a growth-stage company backed by world-class venture capital investors and AI infrastructure industry leaders. Our technology, purpose-built for AI, has garnered over 140 patents and is trusted by more than 30% of Fortune 50 enterprises, as well as the world’s leading hyperscalers, neoclouds, and AI innovators. Our team is customer-obsessed and works accountably, boldly, and collaboratively to ensure their success. If we sound like your kind of people, join us! About the Role We’re looking for a People Data Analyst to help us scale how we use data, systems, and AI across the People team. This role sits at the intersection of People, data, generative AI, and technology — owning our people analytics, improving operational processes, and leveraging AI tools to drive smarter, faster decision making. You’ll work closely with People, Finance, and business stakeholders to deliver insights, improve processes, and keep our People operations running smoothly and efficiently.

Requirements

The AI Mindset: 2–4 years of experience in Data Analytics or HR Technology with a proven track record of using LLMs, Agentic Frameworks, or low-code automation (e.g., Zapier, Make, LangChain) to solve business problems.
Systems Expert: High proficiency in connecting APIs and managing data flows between tools like Greenhouse, HiBob, or Deel.
Analytical Skills: Advanced analytical skills with expertise in data visualization tools (Tableau, PowerBI, or AI-native BI tools) and a strong grasp of SQL or Python for data manipulation.
Business Architect: The ability to interview a stakeholder, map a complex business process, and translate that process into a technical logic for an AI agent.
High Bar for Quality: You understand that an AI agent is only as good as the data it accesses; you have an obsessive focus on data accuracy and ethical AI practices.
High attention to detail and a strong focus on data accuracy

Responsibilities

Own People Data & AI Reporting
Build and maintain AI People dashboards (hiring, attrition, compensation, recruiting)
Standardize metrics and reporting structures across functions
Move beyond descriptive reporting to build predictive dashboards. Use AI to forecast attrition, model compensation scenarios, and visualize different scenarios of our talent density.
Connect our People systems (ATS, HRIS, Culture) to agentic AI tools that can crawl, synthesize, and structure raw data into actionable intelligence.
Continuously identify opportunities to replace manual processes with automated, AI-driven solutions
Utilize AI agents to ensure accuracy and consistency of data across all HR systems
Serve as the "Translator" between complex data and business outcomes, delivering QBR and Board-ready visualizations that explain the why behind the numbers.
Integrate, Build, and Deploy Agentic AI in the People Organization
Lifecycle Automation: Design, build, and maintain AI agents to automate employee lifecycle stages, including personalized onboarding paths, hiring coordination, and proactive HR support.
Agentic Workflows: Utilize AI tools and agents to support system improvements and structure. Create agents that interface with People systems (HRIS, ATS, PEO, EOR, Slack) to trigger actions, follow up on tasks, and resolve queries without human intervention.
Continuous Optimization: Meet with HR leaders and business stakeholders to understand the business context and identify opportunities for processes that can be replaced by autonomous agents and AI to maximize efficiency
System Architecture & Intelligence
Data Infrastructure: Own the integrity of our People Data Lake. Ensure AI agents are pulling from "Clean Truths" by automating data hygiene and audit cycles.
AI Tool Scouting: Stay on the bleeding edge of the AI landscape (Agents, LLMs, RAG) to identify new tools that can further streamline HR and Recruiting operations.
Partner Cross-Functionally
Work closely with Finance, FP&A, RevOps, and Operations on reporting and automation needs
Support data requests and help translate data into actionable insights