Data Scientist - Equity Fund

Key Responsibilities: Alpha Generation: Source, clean, and analyze proprietary and alternative datasets to identify non-consensus investment signals. Sector Intelligence: Build and maintain automated trackers for sector-specific KPIs to predict earnings surprises and inflection points. Portfolio Support: Conduct ad-hoc technical analysis on market positioning and factor exposures to optimize risk-adjusted returns.

Technical Requirements: Python Mastery: Expert-level proficiency in the PyData stack (Pandas, Num Py, Scikit-learn, Sci Py). Experience with time-series analysis and back-testing is essential. Database Management: Advanced SQL skills; ability to architect complex queries and manage large-scale relational databases. Data Visualization: Proven ability to communicate complex data through clear, intuitive visualizations (Tableau, PowerBI, or Plotly).Quantitative Rigor: Strong grasp of statistics (regression, hypothesis testing, machine learning) with a focus on avoiding over-fitting and look-ahead bias.

Preferred Qualifications: Pedigree: 1–5 years of experience within a Top-Tier Investment Bank (Equity Research, Quant Strategy) or a Leading Hedge Fund. Domain Knowledge: Solid understanding of financial markets, corporate balance sheets, and macroeconomic drivers.