Data Analyst – Quantamental Research for Public Equities

About the role

We are looking for a Data Analyst to join a public equities investment team that pursues a quantamental strategy, combining alternative data with fundamental research. The role focuses on sourcing, validating and scaling differentiated datasets to improve security selection and deepen insight into company‑specific and industry‑level inflection points.

Key responsibilities

• Build and maintain workflows to ingest, clean, map, and analyze large‑scale structured and unstructured datasets.
• Evaluate alternative data for relevance, integrity, coverage, timeliness, and predictive power.
• Conduct signal testing and back‑testing to determine the dataset’s value to the investment process.
• Collaborate with the investment team to turn raw data into actionable views on revenue trends, KPIs, competitive dynamics, and inflection points.
• Leverage AI agents and automation to accelerate research, tool‑building, and internal processes.
• Support basic three‑statement modeling and connect data findings to fundamental underwriting.

Required profile

• 1–3 years of experience, ideally at an alternative data vendor in research, product, or analytics.
• Strong interest in public‑markets investing and differentiated research.
• Ability to distinguish signal from noise and apply judgment, not just run analysis.
• High ownership, speed, and intellectual curiosity.

Required skills

• Python programming
• SQL querying
• Web scraping and API‑based data collection
• Time‑series analysis
• Statistical testing