Product Manager, Data Analytics

About Vivmark Residential Vivmark Residential exists to set the mark for what home can be. Formed through the merger of AvalonBay Communities and Equity Residential, Vivmark brings together two industry leaders with a shared commitment to excellence, innovation, and delivering exceptional living experiences. Our vision is to be the most trusted and best-performing rental housing company in America - one that continues to get better as it grows. And we’re looking for people who want to help us do it.

As an owner, developer, and manager of more than 180,000 apartment homes in major markets across the US, we have the scale to offer something most companies can’t. At Vivmark, team members move up and across functions, markets, and disciplines, building lasting careers. We invest in team members’ growth, development, and capabilities that make them and us better, and we hold ourselves to the highest standard as an employer.

The best people want to work here. We hope you’re one of them.

We Offer: A competitive benefits package that supports your health, financial well-being, and work-life balance, including medical, dental, and vision coverage, a 401(k) with company match, paid vacation and company holidays, and exclusive team member housing discounts. **The Role** Reporting to the Senior Manager, Data Analytics, the candidate will be responsible for defining, delivering and continuously enhancing Vivmark 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 machine learning 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.

PLEASE NOTE:** Our current onsite work schedule requires attendance from Monday through Thursday each week, with remote work permitted on Fridays. **What You’ll Do

• 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.
• 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 explain ability, compliance, and reliability.
• 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.
• 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.
• Communicates complex analytical concepts in a clear, business-relevant manner for stakeholders at all levels.
• Supports change management, training, and adoption for new analytics capabilities across the organization.

Requirements

• Bachelor’s degree required; degree in Business, Computer Science, Engineering, Analytics, Economics, or related fiel…