Senior Product Manager / Boston, MA (Local only)

Title: Senior Product Manager
Location: Boston, MA (HYBRID) (Local only)
Duration: 12+ Months Contract
Video Interviews

Job Description:
Need to have a strong experience Asset Management background.

Must Have Skills:
Deep asset?management domain experience, specifically supporting investment performance, attribution, benchmarks, and partnering closely with portfolio, performance, or risk teams
Hands on 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 hands on 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.