What do I bring?
• You Should have:
o Proficiency in Python, including libraries like pandas, NumPy, scikit-learn, PyTorch/TF,statsmodels
o Deep hands-on experience in machine learning & data mining, proficiency in algorithms development and ability to work with complex infrastructures
o Good understanding of time-series modeling, forecasting, anomaly detection
o Working exposure to AI/ML & Data Science Algorithm development
o Familiarity with cloud data platforms (AWS preferred) and data lake architecture
o Ability to translate data findings into clear, actionable insights for dashboards or stakeholders
o Strong data fundamentals & demonstrated ability to organize, clean, schematize and process data, as well as good understanding of how to use data science methodologies to solve complex problems
o Will to be a team player
o Ability to effectively communicate in English, both written and spoken
• Desirable to have
o Working experience in Scala, Graph analytics
o Hands-on experience with frontend technologies such as Angular, JavaScript or similar
o Proven experience working with IOT/sensor data
o Working experience in Agile software development (daily scrum, pair sessions, sprint planning, retro & review, clean code and self-organized),configuration, testing and release management
o Experience in container concepts (Docker, Kubernetes)
o Experience in GitLab Continuous Integration & Docker
o Knowledge of Energy & Sustainability domain
o International collaboration & working experience, with distributed virtual teams
What are my responsibilities?
• You take a challenging role in the development of a cloud-based offering with an easy-to-use interface that monitors, analyzes, and helps to optimize energy utilization of the buildings & campuses – via multi-site performance dashboards visualizing historical and near real-time series data for energy consumption, costs, and emissions values.
• You need to develop tomorrow’s data-driven products for buildings, incl. predictive maintenance, prescriptive simulations, anomaly detection, system optimization and forecasts, by understanding & analyzing business requirements by interacting with stake holders
• You will investigate the most appropriate techniques to solve complex problems by assessing diverse mathematical, statistical and AI models
• You have to evaluate & implement advanced data analytics techniques in collaboration with the global Data Analytics team, Software Architects/Engineers and Product Managers.
• You will need to collaborate with Software Engineers to ensure the smooth integration of data science products into global offerings
• You should analyze large volumes of data covering a wide range of information from building operational data to equipment and user behavior data, to identify new patterns through data mining and AI