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We are seeking a highly motivated Investment Data Analyst to support our Equity Research team. This role is ideal for someone with a strong foundation in finance, excellent Python programming skills, and a practical approach to building investment insights using data - without reliance on machine learning or generative AI tools.

You will collaborate closely with research analysts to understand their investment process and deliver data-driven solutions, including Python-based models, Power BI dashboards, and insights derived from traditional and alternative data sources.

Key Responsibilities:

• Work with equity research analysts to understand and support their investment process through data insights.
• Build and maintain Python-based models for company valuation (DCF, 3-statement models, ratio analysis).
• Develop Power BI dashboards to communicate financial and alternative data insights clearly and effectively.
• Extract, clean, and analyze financial and alternative datasets (e.g., S&P Global, Google Trends, Sensor Tower) using Python and APIs.
• Contribute to investment research through custom tools and dashboards focused on equity markets.

Must-Have Qualifications:

• B.Sc in Finance from a top-tier university (e.g., University of Pennsylvania, MIT, UC Berkeley, NYU, etc.).
• Strong proficiency in Python for financial modeling and data analysis.
• Experience performing:
• DCF valuation
• Financial ratios analysis
• 3-statement modeling
• Hands-on experience integrating alternative data sources (e.g., Google Trends, Sensor Tower) with financial datasets.
• Ability to build BI dashboards (preferably Power BI) to support investment insights.
• A practical mindset - no machine learning or generative AI projects. Applications featuring those heavily will not be considered.

Preferred (Nice-to-Have):

• Minor in Computer Science.
• Past projects or research involving company valuation in sectors such as Energy, Consumer, Technology, or Healthcare.

What You'll Gain:

• Exposure to live equity investment strategies and real-world data applications.
• Close collaboration with experienced research analysts.
• The opportunity to build production-grade tools that drive investment decision-making.

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