Data Scientist

About Axross

At Axross, we develop AI-powered HVAC optimization platforms that help industrial clients — including those in pharmaceuticals, semiconductors, and precision manufacturing — monitor, control, and reduce their energy usage. Our systems rely on high-quality, real-time data from IoT devices, sensors and BMS, which power smarter, greener decisions for our clients.

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.

Requirements

• 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.

Qualifications

• 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.

What We Offer?

• 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.

Apply Now

If you’re excited about using data science and AI to solve industrial challenges and drive sustainable solutions, we’d love to hear from you!