Carrier is the leading global provider of healthy, safe and sustainable building and cold chain solutions with a world-class, diverse workforce with business segments covering HVAC, refrigeration, and fire and security. We make modern life possible by delivering safer, smarter and more sustainable services that make a difference to people and our planet while revolutionizing industry trends. This is why we come to work every day. Join us and we can make a difference together.
About this role
The Data Scientist II will work with a multi-disciplinary team to develop high-priority Machine Learning-enabled product features that improve the lives of our customers. The individual will work across a broad portfolio of Carrier digital products, including Abound Health and Sustainability, a cloud-native platform that unlocks siloed building data to create smarter and more resilient spaces that improve occupant and global wellness – and Abound HVAC Performance, a cloud-native application that intelligently monitors connected HVAC systems, providing vital information through a centralized data stream and improved visibility for facility managers.
Conduct exploratory data analysis (EDA) to understand data patterns, trends, and relationships.
Develop and apply machine learning models and algorithms to solve business problems and extract insights from data.
Collaborate with domain experts and stakeholders to define problem statements, data requirements, and success metrics.
Clean, preprocess, and transform data to ensure its suitability for analysis and modeling.
Conduct statistical analysis and hypothesis testing to validate models and draw meaningful
conclusions.
Optimize and fine-tune models for accuracy, performance, and scalability.
Communicate findings, insights, and recommendations to non-technical stakeholders through data visualizations, reports, and presentations.
Stay updated with the latest developments in the field of data science, machine learning, and relevant technologies.
Bachelor’s degree
3+ months of internship experience in Data Science
Preferred Qualifications
Other qualifications you may have that would be beneficial in this role include:
Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.
Ability to work with large datasets and cloud-based environments (e.g., AWS, Azure, GCP).
Excellent problem-solving skills and a proactive approach to tackling complex challenges.
Strong communication skills, with the ability to convey technical concepts to non-technical
stakeholders.
Strong analytical, strategic, and creative problem-solving skills
Experience with data visualization tools (e.g., Tableau, matplotlib, ggplot) to present insights
effectively.
Knowledge of SQL and databases.
Proficiency in programming languages such as Python, R, or Java, and experience with data manipulation libraries (e.g., Pandas, NumPy).
Hands-on experience with machine learning libraries and frameworks (e.g., Scikit-learn, TensorFlow, PyTorch).
A team player with the ability to collaborate effectively with cross-functional teams.
Strong interest in emerging technology, software, and IoT.
Strong interest in working in remote fast-paced environments on distributed teams to help shape and drive scalable growth in AI/ML.