Data Analyst

Bad Twin Capital is hiring a Data Analyst to support deal teams by structuring and analyzing financial, investor, and market data. The role produces analytical outputs and insights for capital raises, fund growth initiatives, M&A transactions, investor screening, and outreach systems.

Responsibilities:

• The Data Analyst will support deal teams by gathering, cleaning, and structuring financial, investor, and market data for use in analysis and decision-making
• Day-to-day responsibilities include building and maintaining data models, performing quantitative and qualitative analyses, and generating insights to support capital raises, fund growth initiatives, and M&A transactions
• The role involves preparing analytical outputs and visualizations for internal stakeholders and client materials, contributing to investor screening processes, and helping refine the firm’s outreach and marketing systems
• The Data Analyst will collaborate closely with Senior Transaction Leads, Marketing, and other Analysts to ensure data-driven execution across mandates

Requirements:

• Candidates should possess strong analytical skills and data analytics capabilities for evaluating financial, investor, and market information
• Candidates should possess knowledge of statistics and data modeling to build robust models and perform quantitative analysis
• Candidates should possess effective communication skills to present complex findings clearly in written reports and presentations
• Candidates should possess proficiency with relevant tools (e.g., Excel, SQL, BI tools, Python/R) and experience working with large datasets
• Bachelor's degree in finance, economics, mathematics, statistics, data science, or a related field
• advanced degrees or certifications are a plus
• Experience in investment banking, private equity, venture capital, asset management, or related financial services is strongly preferred
• Ability to work independently in a remote environment, manage multiple deadlines, and maintain high attention to detail in a fast-paced setting