About the Company

Gramian Consulting is a specialized advisory firm focused on IT professional services and engineering talent. Drawing on a strong foundation in software engineering and leadership, the team supports organizations in hiring professionals who are well aligned with their technical and business needs.

Role Overview

The client is developing a data-centric platform designed to turn complex real-world information into highly accurate, well-structured knowledge. It blends expert research, data validation, and AI-assisted workflows to convert scattered sources into dependable datasets used in downstream products and decision-making.

This position is suited to a careful analyst who can develop and maintain structured knowledge on vehicles and automotive history. The work includes researching factory records, registries, archives, technical references, and other authoritative materials, then converting that information into verified and organized data.

Contract and Work Arrangement

This is a long-term contractor engagement. The role is remote and requires full-time availability, including at least 4 hours of overlap with New York working hours.

Responsibilities

• Investigate and validate vehicle specifications, production data, configurations, and factory records.
• Pull relevant details from primary materials, archives, registries, and technical documentation.
• Assemble and preserve structured automotive datasets with clear citations and source traceability.
• Judge the credibility of sources and reconcile contradictory information.
• Record supporting evidence for every data point entered.
• Use AI-based tools to speed up research while still independently confirming the output.
• Spot missing details, inconsistencies, and areas where data quality can be strengthened.
• Suggest enhancements to data models and classification frameworks when appropriate.
• Work with internal stakeholders to maintain completeness and accuracy.

Requirements

• At least 3 years of experience in research, data analysis, cataloging, archival work, or another detail-heavy field.
• Strong judgment for evaluating source quality, credibility, and trustworthiness.
• Hands-on experience with structured data, spreadsheets, databases, or similar tools.
• High attention to detail and a strong focus on accuracy.
• Good written English communication skills.
• Comfort using AI tools for research, extraction, and summarization tasks.
• Ability to work independently and manage research assignments with little supervision.

Preferred Background

• Exposure to the automotive sector, especially European manufacturers.
• Knowledge of classic, collector, or niche vehicles.
• Ability to read German.
• Background in archives, registries, libraries, or historical research.
• Experience designing taxonomies, ontologies, or structured knowledge systems.
• Basic scripting, database work, or data management experience.

Additional Information

The role focuses on transforming fragmented source material into dependable, traceable automotive knowledge. Candidates should be comfortable combining manual research with AI-assisted workflows while maintaining rigorous validation standards.

Responsibilities

• Investigate and validate vehicle specifications, production data, configurations, and factory records.
• Pull relevant details from primary materials, archives, registries, and technical documentation.
• Assemble and preserve structured automotive datasets with clear citations and source traceability.
• Judge the credibility of sources and reconcile contradictory information.
• Record supporting evidence for every data point entered.
• Use AI-based tools to speed up research while still independently confirming the output.
• Spot missing details, inconsistencies, and areas where data quality can be strengthened.
• Suggest enhancements to data models and classification frameworks when appropriate.
• Work with internal stakeholders to maintain completeness and accuracy.

Requirements

• At least 3 years of experience in research, data analysis, cataloging, archival work, or another detail-heavy field.
• Strong judgment for evaluating source quality, credibility, and trustworthiness.
• Hands-on experience with structured data, spreadsheets, databases, or similar tools.
• High attention to detail and a strong focus on accuracy.
• Good written English communication skills.
• Comfort using AI tools for research, extraction, and summarization tasks.
• Ability to work independently and manage research assignments with little supervision.