Data Analyst

About the role

We are looking for a detail-oriented Data Analyst to support the development of our data foundation and AI-powered platform. The role involves sourcing, researching, structuring, validating, and maintaining data from global sources. You will work closely with AI/ML and technology teams to transform complex and unstructured information into reliable, structured datasets that can support data-driven analysis and AI-based screening.

What you'll do

• Research and source data from company reports, regulatory filings, supplier portals, industry databases, and other approved global sources.
• Collect, extract, structure, and normalize data into defined schemas.
• Work with SQL and spreadsheets to organize, analyze, and validate datasets.
• Use AI tools such as Claude and similar AI platforms to extract, translate, and structure multilingual data at scale.
• Perform data cleaning, quality checks, entity resolution, and error identification.
• Maintain accurate data provenance, including source, date, and confidence level for each data point.
• Monitor data quality and identify inconsistencies, missing information, and changes in source formats.
• Build and maintain standardized supplier/entity profiles and ensure data accuracy across datasets.
• Collaborate with AI/ML and engineering teams to improve data coverage and quality.
• Conduct ongoing research and update datasets as new information becomes available.

What we're looking for

• Data literacy — spreadsheets and SQL; some Python a plus; can structure messy source data into a defined schema.
• Research & sourcing skill across jurisdictions — finding and extracting the right data from reports, filings and portals; strong attention to details
• AI-first working — fluent using Claude and similar to extract, translate and structure at scale, with human judgement on exceptions and QA.
• Comfort with multi-language sources (via AI translation); rigour on provenance (source · date · confidence tier).
• Willingness to learn the carbon / LCA and automotive supply-chain domain; 2–4 years in a data / research / analyst / operations role; volume data collection & QA a strong plus.

Benefits

• Remote opportunity

Skills