Job Closed
This listing is no longer active.
RealPage is a software company that offers solutions for managers and owners of commercial, multifamily, and single-family rental properties. As an employer, the company works to f
Senior Manager, Customer Data Strategy
Location
United States
Posted
108 days ago
Salary
$105.8K - $180.2K / year
Seniority
Lead
Job Description
Senior Manager, Customer Data Strategy
RealPage
This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description The Sr. Manager, Customer Data Strategy is a proven leader responsible for partnering with other Customer Success leadership in scaling the customer success organization. This role oversees the governance, delivery, and continual enhancement of CS metrics, dashboards, segmentation models, and cross‑platform data integrations. As a senior people leader, this role is responsible for developing high‑performing analytics talent, driving operational excellence, and ensuring CS teams have unified, trusted, actionable data to guide customer outcomes and business decisions. Responsibilities - Own and lead the Customer Data Strategy Program, ensuring alignment to CS strategy, operating rhythms, and enterprise priorities. - Lead, coach, and develop a high-performing analytics and visualization team, including hiring, performance management, talent planning, and career development. - Drive governance of CS metrics, maintaining a trusted CS Metrics Canon with clear definitions, ownership, validation rules, and documented standards. - Oversee the full CS dashboard portfolio, ensuring high-quality UX, accuracy, continuous improvement, standardization, and appropriate retirement of outdated assets. - Lead data-integration initiatives assessing potential tools and connecting CS data to Customer Success platforms and tools (e.g., Salesforce, Gainsight, internal CS systems), increasing automation, data freshness, and insight accessibility. - Publish and manage the quarterly roadmap for CS metrics, dashboards, and data governance initiatives, including risks, dependencies, milestones, and cross-functional alignment. - Ensure timely monthly performance metric updates, coordinating with corporate analytics, platform teams, and data engineering partners. - Own CS coverage and segmentation model governance, partnering with analytics and business stakeholders to ensure ongoing accuracy, change control, and adoption. - Oversee documentation of data sources, lineage, transformations, schema impacts, and governance controls to maintain high data quality and reporting stability. - Partner with Communications and Enablement to deliver release notes, training, and adoption materials; maintain SOPs and knowledge assets for all CS data products. Qualifications - Bachelor’s degree in Business, Data Analytics, Information Systems, or related field. - 5+ years in program management, analytics, data governance, or related disciplines. - Experience in Customer Success operations, CS/CX analytics, or complex SaaS data environments. - Demonstrated success leading teams, including hiring, coaching, and performance management, ideally with experience managing fully remote teams in other time zones and countries. - Experience collaborating with BI, data engineering, or analytics product teams. - Proven ability to drive cross-functional initiatives without direct authority. - Strong communication and presentation skills for executive, business, and technical audiences. Knowledge/Skills/Abilities - Strong technical program leadership (roadmapping, risk management, dependency orchestration). - Proficiency with Power BI and similar visualization tools. - Knowledge of data governance, lineage, metadata, and data quality practices. - Ability to influence and drive clarity in complex, cross-functional environments. - Understanding of Customer Success metrics, segmentation, coverage models, and health scoring frameworks. - Talent development and people leadership capabilities. - Strong proficiency in data analysis and visualization techniques. - Strong ability to leverage data in driving actionable insight and evaluating impact. - Ability to present complex information in an understandable and compelling manner. - Experience managing several projects simultaneously under tight deadlines. - Ability to work closely with all levels of the organization, to elicit cooperation from a wide variety of sources, including management, executives, and others. Physical Demands and Working Conditions - Regular computer use, review of detailed information, virtual collaboration across time zones, and engagement with global teams. - Vision requirements include close vision, color differentiation, and focus adjustment. Pay Range USD $105,800.00 - USD $180,200.00 /Yr.
Job Requirements
- Bachelor’s degree in Business, Data Analytics, Information Systems, or related field.
- 5+ years in program management, analytics, data governance, or related disciplines.
- Experience in Customer Success operations, CS/CX analytics, or complex SaaS data environments.
- Demonstrated success leading teams, including hiring, coaching, and performance management, ideally with experience managing fully remote teams in other time zones and countries.
- Experience collaborating with BI, data engineering, or analytics product teams.
- Proven ability to drive cross-functional initiatives without direct authority.
- Strong communication and presentation skills for executive, business, and technical audiences.
- Knowledge/Skills/Abilities
- Strong technical program leadership (roadmapping, risk management, dependency orchestration).
- Proficiency with Power BI and similar visualization tools.
- Knowledge of data governance, lineage, metadata, and data quality practices.
- Ability to influence and drive clarity in complex, cross-functional environments.
- Understanding of Customer Success metrics, segmentation, coverage models, and health scoring frameworks.
- Talent development and people leadership capabilities.
- Strong proficiency in data analysis and visualization techniques.
- Strong ability to leverage data in driving actionable insight and evaluating impact.
- Ability to present complex information in an understandable and compelling manner.
- Experience managing several projects simultaneously under tight deadlines.
- Ability to work closely with all levels of the organization, to elicit cooperation from a wide variety of sources, including management, executives, and others.
- Physical Demands and Working Conditions
- Regular computer use, review of detailed information, virtual collaboration across time zones, and engagement with global teams.
- Vision requirements include close vision, color differentiation, and focus adjustment.
- Pay Range
- USD $105,800.00 - USD $180,200.00 /Yr.
Related Guides
Related Categories
Related Job Pages
More Data Scientist Jobs
Data Scientist I – Applied AI
Lantana Consulting GroupTransforming healthcare through health information.
• Uses analytic and visualization techniques to support data-informed decision-making • Designs and builds AI-powered applications and tools • Works closely with subject-matter experts and senior technical staff • Prototype, build, and deploy AI tools that solve real-world problems • Create visualizations and conduct analyses using statistical techniques and machine learning • Present findings and insights to diverse audiences
• Modeling complex enterprise problems • Discovering enterprise insights • Identifying opportunities using statistical and machine learning algorithms • Integrating and preparing datasets • Leading discovery processes with stakeholders • Making strategic recommendations for data collection and integration • Developing innovative approaches to solve analytics problems
• Own and operate machine learning models that run in production, including monitoring, debugging, and iterative improvement. • Develop, train, and optimize models used in a real-time or near-real-time bidding and decisioning system. • Work with stakeholders to clarify ambiguous problems, define success metrics, and translate business needs into technical solutions. • Design and implement feature engineering pipelines, balancing model performance, latency, and maintainability. • Write production-quality Python code (not just notebooks) and collaborate with engineering on deployment, CI/CD, and system design. • Analyze model behavior using logs, metrics, and offline analysis to identify performance issues and opportunities. • Contribute to data pipelines and infrastructure where needed (e.g., ETL, materialized tables, model inputs). • Make thoughtful tradeoffs between something that is “theoretically optimal” and something that is reliable, fast, and shippable.
Flood Modeler
Jupiter IntelligenceJupiter is the trusted leader in climate risk analytics, turning sophisticated climate science into actionable data.
This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Jupiter seeks a highly skilled Flood Modeler (contract), with a specialized focus on development and execution of shallow water flood models to support our high-resolution flood modeling pipelines. The purpose of this role is to develop and deploy complex modeling frameworks to simulate and predict flood risk on commercial cloud platforms. This role will involve: - Deploying algorithms for numerical simulation/prediction of flood risk resulting from rainfall, river flow, and coastal storm surge. - Troubleshooting complex algorithms. - Applying code iteratively to test new settings. - Contributing to process workflows. - Assuring quality of output. This role is a critical piece of the team delivering data that forms the backbone of Jupiter products. Qualifications - Master’s degree in Civil/Environmental Engineering, Coastal Engineering, Water Resources, Fluid Mechanics, Hydrology or related field. - Bachelor's degree plus 3-5 years experience also considered. Requirements - 2-dimensional flood model design and deployment (e.g. HEC-RAS, LISFLOOD, TUFLOW, Telemac, or similar). - Model parameter optimization. - Model validation and verification. - Geospatial data processing (QGIS, ArcGIS). - Strong knowledge of Python and experience with libraries such as NumPy, GDAL, Rasterio, Xarray, and Pandas. - Familiarity with software engineering best practices and cloud computing. - Fortran experience a plus. - Experience modeling channel, coastal and floodplain inundation hydrodynamics. - Experience scaling computational methods for large-scale processing (Docker containers, Kubernetes, AWS EC2, Dask, multiprocessing). Benefits - $50 - $55 an hour.




