Sector Data Scientist

Thurn Partners; New York (NY); On-site; USD 120,000 - 180,000; Full time

Job summary

Thurn Partners, a leading global investment firm, is expanding its sector-focused data science capability to embed data directly into the investment research process. The team works alongside investors to apply rigorous analytics to large, complex datasets, generating differentiated, decision-ready insight.

This role suits a data scientist who already thinks like an investor: translating research questions into analytical problems and delivering clear answers that move a decision.

Qualifications

• Strong interest in markets and investing, with curiosity to find data-driven edge.
• Ability to translate research questions into analytical problems.
• Experience with large, complex, or unstructured datasets.
• 2+ years in data science, quantitative research, or statistics.

Responsibilities

• 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 trends, and separate signal from noise.
• Identify drivers across companies and sectors tied to earnings and business metrics.
• Build and validate signals through rigorous statistical and time-series testing.
• Deliver concise, decision-ready outputs (dashboards, written summaries, forecasts).
• Help build scalable datasets and analytical frameworks for decision support.

Skills

Advanced Python

Pandas

SQL

Statistical modeling

Time-series analysis

Unstructured data handling

Investment understanding

Alternative data experience

Education

Bachelor's degree in statistics, computer science, or related quantitative field

Tools

Python libraries (NumPy, SciPy)

SQL databases

Job description

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