Data Scientist

At Axross, we build advanced AI-powered HVAC solutions to optimize energy efficiency in industries such as pharmaceuticals, semiconductors, and precision manufacturing. Our cutting-edge systems help manufacturers better control their production environments while reducing energy consumption, leading to significant cost reductions and supporting environmental sustainability.

The Role

Roles And Responsibilities

• Develop and implement advanced machine learning models (e.g., reinforcement learning, supervised learning) for real time optimization of HVAC systems.
• Work with dynamic simulation models to predict and optimise the performance of industrial systems.
• Analyse large datasets, including plant and environmental data such as temperature, humidity, and energy consumption metrics.
• Build and refine predictive models for energy demand forecasting and optimise control strategies across different industrial applications.
• Collaborate with cross-functional teams (AI engineers, product managers) to deploy models in production environments.
• Design and evaluate experiments to test and validate model performance, ensuring alignment with energy efficiency goals.
• Continuously enhance models to improve prediction accuracy and system control.
• Present findings, analysis, and insights to both technical and non-technical stakeholders.
  
  

• Have at least 2 years' experience with ETL processes and model optimization techniques like feature selection, hyper-parameter tuning, and model validation.
• Proficient in programming languages like Python, R, or Java, with a strong foundation in designing algorithms using various data structures.
• Solid understanding of dynamic simulation models and / or digital twins for system optimization.
• Experience with cloud platforms (e.g., Microsoft Azure, AWS) for deploying AI models.
• Strong analytical thinking, problem-solving skills, and attention to detail.
• Excellent communication skills with the ability to convey complex data insights to a diverse audience.
• Deep understanding and hands-on experience with predictive modelling algorithms like logistic regression, neural networks, decision trees, and heuristic models.
• Ability to work efficiently with different teams and independently learn new concepts or techniques.
  
  

• Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, or a related field.
• Experience in energy optimization, manufacturing, or industrial IoT projects is an advantage.
• Knowledge of reinforcement learning and control theory is highly desirable.
  
  

• The opportunity to work on cutting-edge AI projects with real-world impact.
• A collaborative and innovative work environment.
• Competitive salary and benefits.
• Career growth opportunities in a fast-growing industry focused on sustainability and innovation.