Hybrid Project Manager/Scrum Master

at Johnson Controls

• Job title: Project Manager/Scrum Master
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: $85,000 - $110,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: Azure, IoT, Numpy, Pandas, Python, Scikit-Learn, SDLC, SQL, Tableau, Tensorflow
• Location requirements: Hybrid, Milwaukee, United States

About the role

• Project Manager/Data Analyst managing AI/ML projects for building automation and energy optimization at Johnson Controls. Collaborating with data science, engineering teams, and business stakeholders.

Responsibilities

• Coordinate and track multiple AI/ML projects from initiation through deployment, ensuring timelines and deliverables are met
• Facilitate communication between data scientists, engineers, product managers, and business stakeholders
• Organize and lead project meetings, prepare agendas, document decisions, and track action items
• Maintain project documentation including requirements, specifications, timelines, and status reports
• Monitor project risks and dependencies, escalating issues proactively to ensure project success
• Support sprint planning, backlog grooming, and agile ceremonies for AI development teams
• Prepare executive-level presentations and dashboards showcasing project progress and AI initiative ROI
• Coordinate user acceptance testing (UAT) and pilot programs for new AI solutions
• Conduct exploratory data analysis (EDA) on sensor data, building performance metrics, and equipment telemetry
• Create data quality reports and identify data gaps, anomalies, or inconsistencies that impact ML model development
• Build dashboards and visualizations to communicate insights from building automation systems and IoT devices
• Support data scientists by preparing datasets, performing feature engineering, and conducting statistical analyses
• Analyze model performance metrics and create reports on model accuracy, drift, and business impact
• Develop automated reporting solutions for recurring analysis and KPI tracking
• Collaborate with data engineering teams to ensure data pipelines meet analytical requirements
• Perform ad-hoc analyses to support business questions and AI use case identification
• Morning standup meetings with data science and engineering teams
• Analyzing datasets to support ongoing ML model development
• Updating project trackers, timelines, and status reports
• Creating visualizations and reports for stakeholder meetings
• Coordinating across teams to resolve blockers and dependencies
• Conducting data quality assessments and preparing datasets for modeling
• Documenting project decisions, requirements, and technical specifications
• Preparing presentations for leadership reviews and project updates

Requirements

• Bachelor's degree in Data Science, Computer Science, Engineering, Statistics, Business Analytics, or related field
• 3+ years of experience in project coordination, data analysis, or similar roles
• Experience working with technical teams or supporting software/AI development projects
• Demonstrated ability to manage multiple priorities in a fast-paced environment
• Strong proficiency in SQL for data extraction, transformation, and analysis
• Solid experience with Python or R for data manipulation and statistical analysis (pandas, numpy, matplotlib, seaborn)
• Expertise in data visualization tools such as Tableau, Power BI, or similar platforms
• Experience with exploratory data analysis, statistical testing, and data quality assessment
• Ability to work with large datasets and understand database structures
• Proficiency in Excel including pivot tables, advanced formulas, and data modeling
• Familiarity with project management methodologies (Agile, Scrum, Waterfall)
• Experience with project management tools (Jira, Asana, Monday.com, MS Project, or similar)
• Understanding of software development lifecycle (SDLC) and ML model development processes
• Basic understanding of machine learning concepts and model development lifecycle (preferred)
• Exposure to AI/ML tools and frameworks (scikit-learn, TensorFlow, Azure ML) (preferred)
• Familiarity with MLOps practices, model monitoring, and deployment processes (preferred)
• Knowledge of time series analysis or IoT data analytics (preferred)

Benefits

• Competitive compensation including base salary and performance bonus
• Comprehensive benefits package (health, dental, vision, retirement)
• Professional development budget for certifications and training
• Flexible work arrangements with hybrid/remote options
• Collaborative culture that values innovation and continuous improvement
• Opportunity to work on meaningful projects impacting sustainability and energy efficiency
• Career growth support with clear advancement pathways