Data Operations Associate - AI & Energy Data

Parisi Labs, Inc.•New York, NY

3d•$30 - $40•Hybrid

About The Position

Parisi Labs is building foundational world models for physical industry, focusing initially on energy. We are developing models that learn how complex physical systems behave and reuse that understanding across forecasts, scenarios, and operational decisions. We combine historical and live data with operational context, integrating machine learning research, data infrastructure, and software engineering. We are seeking a Data Operations Associate, on a contract or full-time basis, to source, clean, and validate energy data, with an initial focus on 'Ask The Grid,' a live product for exploring the power grid, its markets, and its assets. This role involves using AI-assisted research and coding to transform scattered information into dependable records and repeatable workflows. Key aspects include exercising judgment on data provenance, identifying errors, and deciding on verification, correction, or escalation processes. The associate will collaborate with founders and the data engineering team on scoping work, owning sourcing and validation tasks, and integrating results into products. Students, recent graduates, and early-career candidates are encouraged to apply, with projects, independent research, and freelance work being acceptable demonstrations of required skills.

Requirements

Hands-on AI use: ability to use tools like Claude, ChatGPT, or AI coding assistants for real work and explain contributions and checks.
Sound judgment regarding source reliability, entity matching, conflicting evidence, and uncertainty.
Ability to break down ambiguous tasks into steps, investigate discrepancies, and ask focused questions.
Practical Python or SQL skills for cleanup, investigation, and simple automation, including with AI assistance.
Careful documentation and clear communication about decisions, quality checks, and limitations.
Curiosity about energy, infrastructure, geography, or complex real-world systems.
No particular degree or minimum number of years of experience required; evidence of useful work, clear thinking, and independent follow-through is valued.

Responsibilities

Find and evaluate public datasets, reports, websites, and APIs; document their coverage, definitions, freshness, and limitations.
Research and enrich energy-asset records with traceable sources and clear treatment of unknowns.
Clean, standardize, deduplicate, and reconcile names, identifiers, units, and locations across sources.
Investigate missing or inconsistent data, trace the cause, and make corrections or escalate unresolved questions with evidence.
Build lightweight Python, SQL, or AI-assisted extraction and validation workflows that another team member can inspect and run.
Maintain clear documentation and follow-through on data requests, checks, and completed work.