Quantitative Data Analyst

Role Overview:

We are seeking a Quantitative Data Analyst to manage the quality and usability of quantitative datasets driving our investment workflows. This role ensures data integrity while supporting critical research and production processes within a collaborative culture focused on professional growth.

Key Responsibilities:

• Data Domain Ownership: Become an expert in key quant datasets (market data, fundamentals, corporate actions, identifiers) to understand their structure, lineage, quirks, and usage in research/production workflows.
• Dataset Onboarding: Lead end-to-end onboarding including profiling, schema validation, identifier mapping, cross-source reconciliation, documentation, and productionization support.
• Automation & Monitoring: Build automated data validation processes (completeness, timeliness, outliers) using code-based solutions. Create clear quality metrics and dashboards to monitor staleness, missing series, and mapping breaks.
• Anomaly Investigation: Investigate data anomalies impacting output: triage issues, isolate root causes, quantify impact, coordinate remediation, and write preventative code.
• Development: Write Python scripts, pipelines, and utilities (using pandas, NumPy) to automate workflows. Collaborate with quant developers to harden solutions for production use.
• Documentation & Operations: Maintain high-quality documentation and operational runbooks covering definitions, assumptions, troubleshooting guidance, and conventions across the data ecosystem.
• Data Maintenance: Perform routine checks, backfills, and improvements as vendor schemas or business requirements evolve.

Collaboration:

Engage constructively with internal teams and external vendors to address data issues or evaluate new sources. Work effectively in a small, close-knit team with direct stakeholder interaction.