Coordinate work across data scientists, data engineers, software engineers, ML engineers, product managers, and business stakeholders.
Facilitate sprint planning, standups, retrospectives, status reviews, demos, and project working sessions.
Identify blockers early, drive resolution, and escalate decisions when necessary.
Ensure that project documentation, requirements, assumptions, and decisions are current and accessible.
Provide concise, regular reporting on progress, risks, dependencies, and expected outcomes.
MLOps and Production Readiness Help Track requirements for reproducibility, versioning, testing, deployment, monitoring, and documentation.
Help coordinate model release readiness, production handoffs, and post-deployment follow-up.
Ensure teams consider data quality, model performance, drift, reliability, security, and support ownership.
Help establish repeatable processes for model promotion, retraining, monitoring, incident response, and model retirement.
Process Improvement and Operating Rhythm Help create lightweight, scalable operating processes for the Data Science organization.
Help develop templates, dashboards, meeting cadences, and documentation standards that improve team effectiveness.
Help identify recurring delivery issues and recommend improvements to processes, tools, roles, or decision-making.
Qualifications
Required
5+ years of experience in technical project management or related delivery role.
Demonstrated experience managing data science, machine learning, analytics, or other highly technical projects.
Experience coordinating cross-functional teams like Data Science, Engineering, & Product functions.
Ability to understand technical discussions involving data pipelines, experimentation, model evaluation, APIs, deployment, and production support.
Strong project management skills, including planning, prioritization, dependency management, risk management, and status reporting.
Excellent written and verbal communication skills.
Ability to operate effectively with ambiguity and bring structure to complex, evolving work.
Strong attention to detail and follow-through.
Experience working in Agile, Scrum, Kanban, or similar delivery environments.
Hands-on experience on how to use AI in workflows effectively and responsibly.
Preferred
Strong understanding of the data science and machine learning lifecycle.
Experience with MLOps, ML platforms, or production machine learning systems.
Familiarity with model deployment, model registries, experiment tracking, CI/CD, workflow orchestration, model monitoring, data quality monitoring, and retraining processes.
Familiarity with responsible AI, model risk management, privacy, explainability, bias, or regulatory considerations.
Technical background in data science, computer science, engineering, analytics, mathematics, or a related discipline.
SALARY AND BENEFITS RealPage provides a competitive salary package along with a comprehensive benefit plan that includes:
Health, dental, and vision insurance.
Retirement savings plan with company match.
Paid time off and holidays.
Professional development opportunities.
Performance-based bonus based on position.
Compensation may vary depending on your location, qualifications including job-related education, training, experience, licensure, and certification, that could result at a level outside of these ranges. Certain roles are eligible for additional rewards, including annual bonus, and sales incentives depending on the terms of the applicable plan and role as well as individual performance. Equal Opportunity Employer: RealPage Company is an equal opportunity employer and committed to creating an inclusive environment for all employees.
Pay Range
USD $94,700.00 - USD $161,300.00 /Yr.
