Product Manager C2C contract Asset Management

Product Manager- Asset Management

Boston, MA

6+ Months

 

Need local

 

Need only ( USC/ GC HOLDER)

 

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 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.