Forward Deployed Research Analyst

About the Role We are building a small, high-caliber team of Forward Deployed Research Analysts with backgrounds spanning fundamental equity research, portfolio management, quantitative research, data science, and investment technology. This role sits at the intersection of investment research, technology, and applied AI. You will work directly with sophisticated investment teams to understand how they conduct research, analyze companies, evaluate opportunities, and make investment decisions, then help transform those workflows using AI. The platform is deployed directly within each client's cloud environment, enabling clients to maintain control over their data, infrastructure, security, and governance. As a Forward Deployed Research Analyst, you will work alongside portfolio managers, research analysts, and senior investment professionals to develop a deep understanding of their existing processes and build AI-enabled workflows that meaningfully improve how they operate. This is not a traditional equity research role, nor is it a traditional technology role. You will serve as the bridge between investment professionals, product teams, and engineers, translating complex research workflows into practical AI capabilities while helping shape the evolution of the platform. This is a 4 days in office position, Wednesdays are remote. Key Responsibilities Embed with Investment Teams and Drive AI-Led Transformation Work directly with portfolio managers, research analysts, and senior investment professionals to understand how they conduct research and make investment decisions. Develop a deep understanding of clients' research processes, investment frameworks, data sources, and existing technology stacks. Identify high-leverage opportunities where AI can automate manual work, augment investment analysis, or fundamentally improve existing processes. Design and implement production-grade AI workflows that can be integrated into clients' day-to-day research and investment activities. Transform Investment Research Workflows with AI Apply your investment and financial markets expertise to identify where AI can have the greatest practical impact. Help clients rethink workflows across areas such as fundamental research, idea generation, company analysis, financial modeling, earnings analysis, portfolio monitoring, risk, and data analysis. Translate complex investment questions and processes into structured workflows that AI agents and models can effectively execute. Build, test, and continuously improve these workflows based on feedback from investment professionals and real-world usage. Bridge Investment Expertise and Engineering Partner closely with engineering and product teams to translate client needs into AI agents, skills, data connectors, and product capabilities. Communicate how investment professionals think, analyze information, and make decisions so technical teams can build solutions that accurately reflect institutional investment workflows. Help define requirements for new capabilities based on direct exposure to client challenges. Serve as a domain expert connecting investment research problems with technical solutions. Shape the Product Become a daily power user of the platform and develop a detailed understanding of its capabilities. Gather structured, actionable feedback from client engagements and communicate what is working, what is missing, and where the product can improve. Partner with product and engineering teams to help prioritize new features and functionality. Identify recurring challenges across client engagements that can be solved through scalable product improvements. Build Research Playbooks and Institutional Knowledge Develop reusable AI-enabled workflows and best practices across investment research, portfolio management, risk, data science, and investment technology. Contribute to a growing library of skills, agents, and research playbooks that can be deployed across investment organizations. Capture best practices from individual client engagements and translate them into scalable capabilities. Help build an institutional knowledge base connecting data, research, risk, technology, and investment decision-making. Requirements Experience & Seniority 3 to 7 years of professional experience in a core equity research function at a top-tier hedge fund, asset manager, sell-side research firm, RMS or financial data vendor platform, or institutional investment fund. Strong understanding of fundamental equity research, company analysis, financial markets, and institutional investment workflows. Experience working with or alongside portfolio managers and senior investment professionals is highly valued. Ability to quickly understand complex investment processes and identify opportunities to improve or transform them. Applied AI Experience Demonstrated hands-on experience building with AI, rather than simply using commercially available AI tools. Experience completing multiple practical AI projects, which may include: GitHub repositories containing research-focused AI skills, agents, or applications. AI-enabled investment research workflows. Personal or professional side projects leveraging LLMs or other AI technologies. Other examples demonstrating practical experimentation and a genuine interest in applying AI to investment research. Strong curiosity around emerging AI capabilities and a willingness to experiment, build, test, and iterate. A builder mentality with an interest in using technology to solve real investment research problems. Financial Data & Technical Skills Hands-on experience working with leading financial data and research platforms such as Bloomberg, Visible Alpha, FactSet, PitchBook, Capital IQ, or similar tools. Strong understanding of how investment professionals source, analyze, and incorporate financial and alternative data into their research processes. Ability to understand how financial data, research content, and technology can be connected to create more effective investment workflows. Comfortable partnering closely with technical teams to translate financial problems into AI-powered workflows, agents, skills, and data integrations. Technical fluency is important, but candidates do not need to come from a traditional software engineering background. Client-Facing & Communication Skills Ability to build trust and credibility quickly with sophisticated investment professionals. Strong ability to ask the right questions, uncover underlying problems, and navigate unstructured or ambiguous conversations. Comfortable engaging directly with senior investors, portfolio managers, research leaders, and C-suite executives at leading hedge funds and investment firms. Excellent communication skills with the ability to translate effectively between investment professionals, product teams, and engineers. Ability to operate independently in client-facing environments while representing the company with a high degree of professionalism. The salary for this position is between 200-250k + Equity Talent Mappers