Product Manager, Data Analytics

At Equity Residential, we're dedicated to creating thriving communities, and we invite you to be part of our team. Embracing values like Diversity, Sustainability, and Total Wellbeing, we foster a workplace culture of authenticity and collaboration.

How We Deliver a Winning Performance:  

• Question Authority 
• Walk the Talk
• Share Knowledge
• Listen, not just Hear
• See the Glass Half Full
• Take Educated Risks
• Enjoy the Ride
• Share the Spotlight
• Do the Right Thing
• Test Your Limits 

We Care About Your Total Wellbeing:

• Physical Wellbeing: Medical, dental, and vision care 
• Social Wellbeing: 9 paid holidays, annual vacation time, paid sick leave, new parent benefits
• Financial Wellbeing: 401(k) Retirement Savings Plan, Rent Discounts, Competitive Compensation
• Community Wellbeing: Paid Community Service Hours
• Career Wellbeing: Leadership Development
• Learn more about our Total Wellbeing program here.

What You’ll Be Doing:

The Product Manager, Data Analytics defines, delivers, and continuously enhances  Equity Residential’s analytics and machine-learning–enabled products. This role sits at  the intersection of data science, software engineering, and business strategy,  translating analytical insights into scalable systems and partnering with technical teams  to operationalize ML models into production-grade applications. 

The ideal candidate brings a blend of product management discipline, technical  fluency in machine learning and data pipelines, and strong program management  skills. This role collaborates closely with the Senior Software Engineer, data scientists,  and business partners to build intuitive, reliable products that drive measurable impact  on pricing, forecasting, and operational decision-making. 

 

ESSENTIAL FUNCTIONS:

Product Strategy & Roadmap 

• Collaborates with business, analytics, and engineering teams to define the vision,  strategy, and long-term roadmap for data and machine learning products. 
• Translates complex pricing, forecasting, and operational needs into clear product  requirements, user stories, and acceptance criteria. 
• Leads prioritization across competing business and technical needs, managing  backlogs and release plans. 
• Serves as product spokesperson and subject matter expert for analytics  capabilities across the enterprise. 

Machine Learning & Technical Collaboration 

• Works directly with data scientists to understand and refine model outputs,  feature relevance, performance metrics, and constraints. 
• Applies strong technical knowledge of machine learning workflows, pipelines,  APIs, and model monitoring to guide product direction and evaluate trade-offs.
•  Partners with the Senior Software Engineer – Data & Analytics Products to  operationalize models into user-facing applications and enterprise systems. 
• Ensures all ML-driven product features emphasize explainability, compliance,  and reliability. 

Program Management & KPI Governance 

• Defines and tracks key KPIs (e.g., model accuracy, revenue lift, adoption, system  reliability) to measure product performance and business impact. 
• Establishes a structured cadence for reviewing KPIs with cross-functional  partners and initiating corrective actions or enhancements. 
• Drives successful delivery of milestones across pilots, MVP releases, and  product iterations. 
• Leads retrospectives and drives continuous improvement of analytics workflows,  model governance, and product execution processes. 

Stakeholder Partnership & Communication 

• Acts as the bridge between data scientists, software engineers, IT, Pricing, and  Operations teams. 
• Facilitates workshops, demos, feedback sessions, and cross-functional updates  to maintain alignment and transparency.