Senior Data Specialist

Job Title: Data Partner, Research Data Integrity

Compensation: Up to $500k total compensation - varies on level

Location: New York, NY (4 days onsite)

A global, data-intensive investment platform building AI-native research infrastructure to power high-conviction decision-making.

This organization operates at the frontier of quantitative research and applied AI, combining large-scale structured and unstructured data with advanced modeling systems. Data quality is not a back-office function here it is foundational to how decisions are made. As AI becomes more deeply embedded into research workflows, ensuring correctness, reliability, and traceability of data inputs is mission critical.

We’re hiring an AI Data Partner to sit directly alongside research and AI teams, owning the datasets that power production-grade analytical and LLM-driven systems.

Instead, you will be responsible for ensuring that complex financial and alternative datasets are correct, validated, and production-ready. You will investigate inconsistencies, design durable quality controls, reconcile cross-source discrepancies, and build benchmark datasets used to evaluate AI system outputs.

Your work will directly influence the reliability of AI-driven research workflows operating in real decision environments.

• Own critical datasets end-to-end, from acquisition through validation and production deployment
• Evaluate external and alternative data vendors, identifying methodology risks and structural weaknesses
• Reconcile discrepancies across multiple providers and internal systems
• Design validation logic, anomaly detection checks, and quality control thresholds
• Build benchmark datasets used to measure AI and LLM output correctness
• Investigate data breaks and implement scalable, durable fixes
• Determine where automation is appropriate versus where expert review is required
• Partner with research and AI teams to translate ambiguous analytical questions into reliable, structured inputs

• Experience owning high-stakes datasets within financial services, research, risk, regulatory, or alternative data environments
• Demonstrated ability to diagnose and resolve complex data inconsistencies
• Strong understanding of reconciliation, validation frameworks, and data quality controls
• Comfort working with messy, external, or unstructured data sources
• Ability to clearly explain failure modes and implement preventative solutions
• Proficiency in SQL and Python
• Experience in institutional investment environments, financial data providers, or risk/compliance functions strongly preferred

• Exposure to datasets used in AI or LLM-driven systems
• Experience operating in research-driven environments where data correctness directly impacts decision quality

• Operate at the intersection of AI systems and real-world decision quality
• High-ownership role embedded with research and technical teams
• Tackle complex, ambiguous data challenges with measurable impact
• Contribute to AI-native research infrastructure at scale
• Competitive compensation and performance upside

People In AI partners with world-class AI-driven organizations to build exceptional technical teams. We connect high-caliber talent with impactful opportunities across machine learning, data, and infrastructure. If you’re exploring roles where data integrity and AI intersect in meaningful ways, we’d love to speak with you.