AI Data Specialist - Asset Management

I Squared Capital (“ISQ”) is an independent global infrastructure investment manager with over $60 billion in assets under management. The firm invests across a diverse range of sectors, including energy, utilities, transport and logistics, digital, social, and environmental infrastructure throughout the Americas, Europe, and Asia.

I Squared Capital’s mission is to transform infrastructure that powers communities and economies globally. Headquartered in Miami, ISQ has more than 350 employees across offices in Abu Dhabi, London, Munich, New Delhi, São Paulo, Singapore, Sydney, and Taipei. The firm’s portfolio includes over 100 companies, representing more than 110,000 portfolio company employees and assets spanning over 115 countries.

ISQ’s investment platform spans Global Equity, Growth Markets, Energy Transition, Infrastructure Credit, and InfraTech, with a focus on technology related to infrastructure.

For more information please see: https://isquaredcapital.com

We are seeking a curious, technically skilled recent graduate to join our US Asset Management team in Miami. As part of a new internal AI and automation initiative at ISQ, you will help transform how investment teams work by identifying opportunities to streamline processes across the investment lifecycle. Working alongside investment professionals, you will map manual and repetitive workflows, develop responsible, well-governed AI and automation solutions and tools that allow the team to spend more time on high-value analysis and investment decision-making.

• →Identify and prioritize AI opportunities
  Partner with investment professionals to map existing workflows, identify manual and repetitive tasks, and maintain a prioritized pipeline of AI and automation initiatives based on business impact, implementation effort, and risk.
• →Design, develop, and deploy AI solutions
  Build proof-of-concept and production-ready solutions using a combination of low-code/no-code platforms (e.g., Microsoft 365 Copilot, Power Automate, Power Apps) and custom development (e.g., Python, LLM APIs). Deliver solutions such as research summarization, automated data collection and cleansing, screening and monitoring dashboards, and report drafting tools
• →Strengthen data and AI foundations
  Improve data quality, structure, and accessibility to support reliable AI solutions. Ensure data is accurate, appropriately sourced, and managed in accordance with firm governance, privacy, and security standards.
• →Evaluate AI technologies and recommend solutions
  Assess emerging AI tools and vendors, conduct structured pilots, and provide data-driven build-versus-buy recommendations based on functionality, cost, scalability, and risk.
• →Create scalable AI capabilities
  Develop and maintain reusable prompts, templates, automation components, and best practices that enable AI solutions to be adopted and scaled across the investment team.
• →Drive implementation and user adoption
  Transition solutions from prototype to day-to-day use through documentation, user training, support, and continuous improvement based on stakeholder feedback.
• →Measure impact and communicate results
  Track key performance metrics—including time savings, adoption, efficiency gains, and error reduction—and provide regular updates to leadership on the impact of AI and automation initiatives.
• →Ensure responsible and secure AI implementation
  Build solutions in accordance with the firm's AI governance, data privacy, cybersecurity, and regulatory requirements. Partner with Technology, Data, Information Security, Risk, and Compliance teams to ensure solutions are secure, well-governed, and effectively integrated into existing systems.

• Bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, Mathematics, or a related quantitative field, with a strong academic record.
• Working proficiency in Python, with experience or familiarity using large language model (LLM) APIs (e.g., OpenAI, Anthropic) and prompt engineering techniques.
• Experience with or the ability to quickly learn low-code/no-code automation platforms, such as Microsoft 365 Copilot, Power Automate, and Power Apps.
• Strong understanding of data management principles, including sourcing, cleaning, structuring, validating, and interpreting data responsibly.
• Familiarity with cybersecurity, data privacy, and AI governance fundamentals, including awareness of AI-specific risks such as data leakage, prompt injection, and responsible AI practices.
• Strong analytical and problem-solving skills, with the ability to translate business needs into practical AI and automation solutions.
• Excellent communication and interpersonal skills, with the ability to explain technical concepts to both technical and non-technical audiences and confidently present ideas to stakeholders.
• High attention to detail and commitment to producing accurate, reliable outputs, particularly for data and analyses that support investment decision-making.
• Self-motivated, intellectually curious, and comfortable working in a fast-paced environment with ambiguity and evolving priorities.
• Preferred: Experience with SQL and familiarity with cloud-based data platforms or business intelligence tools, such as Snowflake, Microsoft Azure Synapse/Fabric, or Power BI.