Senior Manager, Cloud Scrum Master leading Agile transformation within Cloud Engineering team at Bristol Myers Squibb. Your role is pivotal in scaling Agile practices across various functions.
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
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