Data Scientist - Equity Fund in New York

Energy Jobline ZR; New York (NY); On-site; USD 140,000 - 240,000; Full time

Job summary

Energy Jobline ZR partners with a top quant fund to hire a Data Scientist for the portfolio management team, focusing on translating massive, unstructured datasets into actionable market signals and KPI monitoring. You will build sector trackers, perform ad-hoc analysis of market positioning, and apply Python-based PyData tools to enhance risk-adjusted returns. Strong SQL, visualization skills, and statistical rigor are essential.

Qualifications

• 1–5 years of experience within a top-tier Investment Bank (Equity Research, Quant Strategy) or leading hedge fund.
• Solid understanding of financial markets, corporate balance sheets, and macroeconomic drivers.

Responsibilities

• Alpha: Source, clean, and analyze proprietary datasets to identify signals.
• Sector Intelligence: Build trackers for sector KPIs to predict earnings surprises and inflection points.
• Portfolio Support: Conduct ad-hoc technical analysis on market positioning to optimize risk-adjusted returns.

Skills

Python

SQL

Data Visualisation

Statistics

Time-series

Education

Bachelor's degree in a quantitative field

Tools

Pandas

NumPy

Scikit-learn

Tableau

Power BI

Plotly

Job description

Job Description

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 : 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.

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.