Multifamily Product Analysis - Senior

Freddie Mac•McLean, VA

1d•$108,000 - $152,000

About The Position

The Senior Product Analyst on Freddie Mac’s Multifamily Technology team supports product delivery and business transformation for the Multifamily function within the Capital Markets business line. The role partners with Product Leadership, Product Owners/Managers, business stakeholders, and delivery teams to translate strategy and complex business needs into measurable outcomes, high-quality requirements, and executable work. The analyst leads discovery and analysis to understand customer needs, current workflows, pain points, controls, data flows, and constraints. Using a business-process-first approach, the role defines future-state processes and capabilities, decomposes complex problems into epics, features, and user stories, and ensures backlog items are clear, testable, and ready for estimation and delivery. The position also coordinates data mapping and modelling requirements, defines and tracks product outcomes and KPIs, and identifies risks, dependencies, and decision points. The Senior Product Analyst works across UX, research, Change Management, Engineering, Architecture, Data, Risk/Controls, and other teams to align stakeholders, inform prioritization, and incorporate customer feedback, usability findings, operational insights, and industry trends. The role supports delivery and deployment through story validation, UAT planning and support, Day 1 and operational readiness, process redesign, and controls documentation. It also mentors junior analysts and identifies AI-enabled opportunities while considering governance, risk, controls, and explainability.

Requirements

Bachelor’s degree in Business, Computer Science, Engineering, or a related field, or equivalent experience.
5–7 years of experience in product analysis, business analysis, product operations, or related roles supporting technology delivery and transformation.
Experience in the mortgage, real estate, or broader financial services industry.
Strong proficiency with the Atlassian suite, including Jira and Confluence, or similar agile product management tools.
Demonstrated experience working with agile delivery teams, such as Scrum or Kanban, including backlog refinement, requirements management, and process documentation.
Strong analytical and problem-solving skills, including the ability to synthesize qualitative and quantitative inputs into clear recommendations.
Excellent written and verbal communication skills and strong facilitation skills with senior stakeholders.
Ability to work effectively in ambiguity, manage multiple priorities, and drive alignment across teams.

Responsibilities

Lead requirements and process analysis for complex, cross-functional initiatives, documenting current- and future-state processes, capabilities, and functional needs.
Facilitate stakeholder working sessions to clarify needs, resolve ambiguity, and document decisions, assumptions, and open questions.
Partner with Product and delivery teams to draft and refine epics, features, and user stories, including acceptance criteria, and maintain traceability to outcomes and customer value.
Own backlog readiness for assigned product areas, ensuring items are well-defined, testable, and aligned with intended outcomes and constraints.
Coordinate data mapping and modelling to ensure integration requirements are defined and ready to be modelled.
Define and track product outcomes and KPIs, support measurement planning, and evaluate results after release.
Identify and manage dependencies, risks, and delivery impacts; escalate issues with recommended options and tradeoffs.
Partner with UX and research to incorporate user pain points, usability findings, and journey insights into requirements and prioritization.
Support delivery and rollout, including UAT strategy and support, story validation, Day 1 readiness, operational readiness, and controls documentation where applicable.
Mentor and guide junior analysts in story writing, process modeling, and stakeholder facilitation.
Identify and document AI-enabled opportunities while considering governance, risk, controls, and explainability.