We are currently partnered with a top quant fund that is looking to expand their L/S Equity business by adding a Data Scientist to their portfolio management team. This firm has a top global reputation of a being a top performing quant fund year in and year out.
You will be responsible for transforming massive, unstructured datasets into actionable market insights. Your work will directly influence sector-specific research, market positioning, and the monitoring of critical KPIs that drive P&L.
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, NumPy, Scikit-learn, SciPy). 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.