Role Description Arcana is a portfolio intelligence platform used by hedge funds and asset managers to analyze performance, risk, and portfolio exposures. We’re rethinking the analytical infrastructure institutional investors rely on—and we’re hiring analytically driven problem solvers who want to help shape the future of investment technology. This is not a traditional investment analyst role focused on pitching stocks or building static models. Our Portfolio Analytics Specialists work directly with clients, product, and engineering teams to onboard sophisticated investment firms, solve complex portfolio analytics challenges, and help build institutional-grade financial software. If you enjoy owning projects end-to-end, working closely with institutional investors, and translating analytical problems into scalable workflows and tools, we’d love to talk. Responsibilities - Lead onboarding and implementation projects for hedge funds and asset managers using Arcana’s portfolio intelligence platform - Partner directly with portfolio managers, analysts, risk teams, and operations teams to understand workflows and analytical requirements - Collaborate cross-functionally with product, engineering, and data science teams to improve analytics workflows and platform capabilities - Troubleshoot client issues and drive resolution across analytical, operational, and technical domains - Help shape product direction by identifying recurring client needs, workflow inefficiencies, and opportunities for automation - Clearly communicate analytical insights and platform functionality to sophisticated institutional users Qualifications - Bachelor’s or Master’s degree in Finance, Economics, Engineering, Mathematics, Computer Science, or a related field - Strong academic performance, 3.7+ GPA - Experience with Excel and analytical tools required - Familiarity with Bloomberg, FactSet, Aladdin, or similar financial platforms is a plus - Experience with Python, SQL, or other analytical/programming tools is beneficial but not required - CFA, FRM, or related certifications are a plus - Open to New York, Chicago, or Remote Requirements - 2–5 years of experience in a highly analytical, client-facing, or execution-oriented role within financial services, fintech, or investment technology - Strong project ownership skills with the ability to independently manage initiatives from onboarding through execution - Excellent analytical and problem-solving abilities, including comfort working with large datasets and financial concepts - Strong communication and interpersonal skills, with the ability to explain complex analytical concepts clearly to institutional clients - Familiarity with portfolio analytics concepts such as performance attribution, factor exposures, risk metrics, drawdowns, correlation, and volatility - Demonstrated interest in financial markets, portfolio management, and institutional investment workflows - Highly organized, detail-oriented, and comfortable operating in a fast-paced environment - Ability to work cross-functionally with clients, product managers, engineers, and data teams

• Develop, maintain, and optimize SQL queries, stored procedures, and database scripts • Load, transform, and validate large datasets within SQL Server environments • Support ETL-related workflows, including data extraction, transformation, cleansing, and migration activities • Perform data cleanup and manipulation tasks to improve overall data quality and consistency • Troubleshoot SQL performance issues and optimize complex queries • Collaborate with engineering and business stakeholders to understand data requirements and deliver accurate solutions • Assist with ongoing database maintenance and operational support activities • Ensure data integrity, validation, and reconciliation across systems • Create and maintain technical documentation related to database and ETL processes

• Develop, maintain, and optimize SQL queries, stored procedures, and database scripts • Load, transform, and validate large datasets within SQL Server environments • Support ETL-related workflows, including data extraction, transformation, cleansing, and migration activities • Perform data cleanup and manipulation tasks to improve overall data quality and consistency • Troubleshoot SQL performance issues and optimize complex queries • Collaborate with engineering and business stakeholders to understand data requirements and deliver accurate solutions • Assist with ongoing database maintenance and operational support activities • Ensure data integrity, validation, and reconciliation across systems • Create and maintain technical documentation related to database and ETL processes

• Technical Leadership and Mentorship: Act as a reference for analysts and engineers, promoting development best practices, performing code reviews, and mentoring the team to advance analytical maturity. • Strategic Data Modeling: Design and maintain robust data layers (Silver/Gold) in BigQuery, translating the industry's complex business rules into efficient dimensional models. • Data Engineering Culture: Implement automated testing frameworks, data quality monitoring, and documentation via dbt, ensuring that security and reliability metrics are 100% trustworthy. • Business Interface: Work proactively with Product Managers and functional areas to elicit requirements, investigate root causes of operational pain points, and propose architectural solutions that anticipate needs. • Optimization, Scalability and FinOps: Identify bottlenecks in queries and pipelines, proposing refactors to improve performance and cost efficiency across the Group's large data volumes.