A leading global investment firm is deepening its sector-focused data science capability, embedding data directly into the investment research process. The team works side by side with investors, applying rigorous analytics to large, complex, and often unstructured datasets to generate differentiated, decision-ready insight.
This role suits a data scientist who already thinks like an investor: someone who can take a fundamental research question, translate it into an analytical problem, and return with a clear answer that moves a decision. You will act as a thought partner to portfolio managers and analysts, bringing structure, speed, and statistical rigor to how data informs research and portfolio construction.
The Role:
- Partner with investment teams to understand their research process and pinpoint where data creates an edge
- Design and run analyses across structured and unstructured datasets to test investment theses
- Rapidly assess new datasets for relevance and quality, detect emerging trends, and separate signal from noise
- Identify the operational and fundamental drivers that matter across companies and sectors, tied to earnings and key business metrics
- Build and validate signals through rigorous statistical and time-series testing
- Deliver concise, decision-ready outputs (dashboards, written summaries, forecasts) tailored for senior investors
- Help build and evolve scalable datasets, analytical frameworks, and decision-support tools
Experience/Skills Required:
- Genuine interest in markets and investing, with the curiosity to question consensus and hunt for an informational edge
- Ability to digest fundamental research quickly and turn narratives into data-driven analysis
- Advanced Python (including Pandas) and strong SQL
- Solid grounding in statistical modeling, quantitative analysis, and time-series methods
- Hands-on experience with large, complex, or unstructured datasets
- Prior exposure to investment management, equity research, or buy-side analytics
- 2+ years in alternative data, data science, statistics, or quantitative research
- Bachelor's degree in statistics, computer science, applied mathematics, engineering, economics, physics, or a related quantitative field