About Careertakes

👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Venture Capital & Private Equity; Investment Management; Financial Services.

Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.

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Role Overview

This is a full-time Data Scientist role supporting a long/short equity portfolio team at a confidential client — a top quantitative equity fund. You will turn large, unstructured datasets into robust signals that inform sector research, earnings forecasts, and portfolio positioning. This role sits on the portfolio management team and requires strong quantitative rigor, production-grade Python and SQL skills, and experience working with alternative datasets and time-series backtests.

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What You’ll Do

• Source, clean, and analyze proprietary and alternative datasets to identify non-consensus investment signals and support alpha generation.
• Build automated sector-specific KPI trackers and other tools to detect earnings surprises and inflection points.
• Design and run time-series backtests and validation frameworks that minimize look-ahead bias and overfitting.
• Provide ad-hoc portfolio support: analyze factor exposures, monitor risk, and quantify market positioning impacts on P&L.
• Create clear, production-ready visualizations and dashboards for PMs and research teams.
• Collaborate with engineers and researchers to move research into reproducible, production workflows.

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Technical Requirements

• Expert-level Python proficiency (PyData stack: Pandas, NumPy); experience with time-series analysis and backtesting.
• Advanced SQL skills and experience designing performant queries for large relational datasets.
• Solid machine learning and statistical foundations (regression, hypothesis testing, cross-validation).
• Proven ability to produce intuitive visualizations using Tableau, Power BI, Plotly, or similar.
• Familiarity with data engineering best practices, version control, and reproducible analysis.
• Strong attention to data quality, bias controls, and quantitative validation.

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Preferred Qualifications

• 1–5 years of relevant experience at a top-tier investment bank (equity research, quant strategy), hedge fund, or quantitative firm.
• Domain knowledge of financial statements, sector dynamics, and macro drivers relevant to equity research.
• Experience with alternative / unstructured datasets (web-scraped, satellite, transaction, etc.) is a plus.
• Prior exposure to productionizing research (pipelines, monitoring, deployment) is advantageous.

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Location & Work Authorization

• Location: New York, NY (on-site / hybrid as required by the confidential client).
• Candidates must be legally authorized to work in the United States.

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Why This Role

• High-impact role where quantitative research feeds directly into live portfolio decisions.
• Work with large, interesting datasets and a team focused on rigorous, reproducible alpha generation.
• Competitive, performance-driven environment at a well-regarded quantitative equity firm.

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Equal Opportunity & Hiring Transparency

Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.

If you have questions about how your data is used, please contact us directly.