THE FUTURE IS WHAT WE MAKE IT.
Senior Advanced Artificial Intelligence Machine Learning Data Scientist
Changi, Singapore
Start your career by making an impact and real connections with some of the most meaningful challenges around. When you join Honeywell, you become a member of our performance culture comprised of diverse leaders, thinkers, innovators, dreamers, and doers who are changing the future.
Make the Best You.
Working at Honeywell is not just creating incredible things. You will collaborate with top minds, grow through continuous learning, and benefit from an inclusive environment that rewards performance and celebrate achievements.
Join Us and Make an Impact.
As a Senior Advanced Artificial Intelligence Machine Learning Data Scientist , your focus will be to optimize HVAC systems, focusing on energy efficiency, predictive maintenance, and indoor environmental control. They analyze data from sensors, building automation systems, and weather forecasts to identify areas for improvement and develop data-driven strategies for energy reduction, cost savings, and extended equipment lifespan
Key Responsibilities:
- Data Analysis & Interpretation: Analyze large datasets from HVAC systems, including time-series data, sensor data, and building automation data.
- Machine Learning: Apply machine learning techniques like regression, clustering, and time-series analysis to predict energy consumption, identify maintenance needs, and optimize system performance.
- Data Visualization: Create visualizations to communicate insights and recommendations to stakeholders.
- Domain Knowledge: Possess a strong understanding of HVAC systems, including different types of HVAC equipment, building automation systems, and energy efficiency principles.
- Statistical Analysis: Perform statistical analysis to identify trends, patterns, and anomalies in HVAC data.
- Problem Solving: Develop and implement data-driven solutions to address specific challenges in HVAC systems, such as energy waste, equipment failures, and indoor comfort issues.
- Predictive Maintenance: Use machine learning models to predict when HVAC equipment may fail, enabling proactive maintenance and reducing downtime.
- Energy Consumption Optimization: Identify opportunities to reduce energy consumption by analyzing HVAC system data and optimizing control strategies.
- Indoor Environmental Control: Use data analytics to optimize indoor comfort by adjusting temperature, humidity, and ventilation settings based on occupancy, weather conditions, and building automation data.
- Fault Detection and Diagnosis: Analyze sensor data to identify and diagnose faults in HVAC systems, leading to faster and more efficient repairs.
- Performance Evaluation: Assess the performance of HVAC systems and identify areas for improvement by comparing actual performance against benchmarks and standards.
- Smart HVAC Systems: Develop and implement intelligent control systems that automatically adjust HVAC settings based on real-time data and occupancy