Product Manager-Asset Management

Role: Product Manager- Asset Management ( USC/ HOLDER)

Target Start Date: Immediately

Location: Local to Boston

Onsite: Hybrid, 4-days per week at the client or PS office is the expectation

Interview Process: 2-3 internal interview rounds, no client round expected

Must Have Skills:

• Deep assetmanagement domain experience, specifically supporting investment performance, attribution, benchmarks, and partnering closely with portfolio, performance, or risk teams

• Handson product experience on investment platforms, with clear ownership of requirements, backlog, and delivery while enhancing and evolving existing systems

• Comfortable working directly with data, including handson SQL and some Python, plus a practical mindset on using AI to improve analysis, requirements, and delivery artifacts

Requirements:

Business & Domain Analysis

• Lead requirements elicitation sessions with business and operations across front to back-office teams in asset management with special focus on investment performance calculations, attribution, portfolio and benchmark data
• Translate complex asset management business processes into user stories, acceptance criteria, and functional specifications
• Map current-state and future-state workflows across front, middle, and back-office operations, identifying gaps and optimization opportunities

Agile Delivery & Part-Time PM (20 40%)

• Facilitate agile ceremonies including sprint planning, stand-ups, retrospectives, and backlog refinement
• Own and groom the product backlog in partnership with the Product Owner stories well-defined, estimated, and prioritized
• Track sprint velocity, manage dependencies, and communicate delivery status to stakeholders and leadership
• Coordinate cross-functional delivery across data engineering, analytics, and QA workstreams

Technical & Data Collaboration

• Write and maintain SQL queries for data validation, reconciliation, and ad hoc analysis supporting performance and benchmark data pipelines
• Build BI visualizations, preferably using Power BI, to drive decision-making and executive readouts
• Support adoption of AI-augmented practices across the SDLC from AI-assisted requirements drafting and test case generation to automated documentation and delivery acceleration

Required Qualifications

• 5+ years as a Business Systems Analyst or equivalent role within asset management or financial services
• Strong understanding of front, middle, and back-office operations trade lifecycle, portfolio accounting, investment performance, reconciliation, client reporting
• Working knowledge of financial instruments and products (equities, fixed income, derivatives, alternatives, ETFs, mutual funds)
• Demonstrated ability to independently drive requirements gathering, stakeholder workshops, and documentation with minimal supervision
• Experience facilitating agile ceremonies and performing planning/coordination in a Scrum or Kanban environment
• Proficiency in SQL for querying, data validation, and analytical support
• Awareness of how AI and automation tools (e.g., GitHub Copilot, LLM-based assistants, AI test generation) are transforming the SDLC, with willingness to champion adoption

Preferred Qualifications

• CFA charter holder or progress toward CFA designation (Level I, II, or III candidate); CIPM, CAIA, or equivalent certifications also valued
• Understanding of investment performance measurement (TWR, MWR, attribution analysis, benchmark construction) and risk measures (VaR, tracking error, Sharpe ratio)
• Experience with Power BI for dashboard development or data visualization
• Working knowledge of Python for scripting, data manipulation, or automation
• Familiarity with cloud data platforms such as Microsoft Fabric, Azure Synapse, Snowflake, or Databricks
• Experience with JIRA, Azure DevOps, or equivalent agile planning tools

What We Value

• Self-starter mindset - you take ownership, anticipate needs, and drive work forward without being asked
• Intellectual curiosity about markets, instruments, and the investment management value chain
• Strong communication skills bridging technical teams and business stakeholders
• Forward-looking perspective on AI in the SDLC - not just awareness, but enthusiasm for experimenting with and integrating AI tools into planning, requirements, testing, and delivery
• Collaborative spirit with a bias toward clarity, transparency, and continuous improvement.