Quantitative Researcher/Data Scientist – Alternative Data | London

Location: London, UK
Compensation: Competitive

We are working with a leading equity investment manager that is expanding its Quantitative & Data Insights team. The firm is seeking a quantitative researcher with a strong background in alternative data, primary research, and experience working directly with portfolio managers and investment analysts.

This role requires the ability to understand and contribute to investment discussions at the stock level, analyzing how data can drive investment theses on individual companies. While prior exposure to equities is beneficial, it is not essential.

Key Responsibilities:

• Analyze alternative data sources, including credit card transactions, job postings, web traffic, and other signals, to generate equity investment insights.

• Work closely with portfolio managers and investment analysts to translate data-driven insights into actionable stock-level research.

• Conduct fundamental research and quantitative analysis to support investment decisions, including portfolio modeling, stress testing, and signal validation.

• Collaborate with data engineers to refine NLP models for processing equity research documents and unstructured data.

• Develop machine learning models to identify patterns in trading and alternative datasets, improving portfolio manager feedback.

• Scrape and analyse unstructured text data to enhance investment insights and portfolio management decisions.

• Produce investor behaviour analysis to refine stock selection, mitigate biases, and optimize execution.

Key Requirements:

• 2–5 years of experience as a Data Analyst, Data Scientist, or Quantitative Researcher, with a focus on alternative data.

• Strong quantitative background, with proficiency in Python, SQL, and data visualization tools.

• Experience working directly with portfolio managers and analysts, with the ability to discuss company fundamentals and translate data into investment insights.

• Strong interest in financial markets, stock selection, and equity investing.

• Experience with interactive visualizations and dashboards (Shiny, Python/R libraries) is a plus.

• Exposure to nowcasting techniques, web scraping, and unstructured data analysis is preferred.

This is an opportunity to be at the intersection of quantitative research and fundamental investing, helping to enhance stock selection and portfolio construction using cutting-edge data science techniques.

To apply, please submit your CV to quantresearch@octaviusfinance.com