Data Scientist – BuildingIQ


Data Scientist

Job Description | Location – Sydney, Australia

BuildingIQ powers technology-enabled services to help building owners/operators achieve balanced energy and operational efficiency, and tenant comfort for any building.  Our machine learning enabled platform analyses a huge amount of power and sensors data to provide real-time feedback and perform optimization tasks to help reduce the amount of consumed energy, provide a platform of descriptive, diagnostic, and predictive analytics to turn large volumes of complex data into actionable insights to improve engineering design and decision-making processes, and also perform baselining of existing buildings.

We are looking for a Data Scientist to be a part of our data science team in Sydney, Australia. You will work across all facets of our organization, performing real world experiments and assisting product management in strategies to make use of our large volume of data and Machine Learning capabilities. In addition, this role will work closely with Software Development to create robust algorithms and frameworks for the rapid expansion of our analytics abilities on our 5i platform.


  • Bachelor or master’s degree in control/mechanical engineering, electrical engineering, or background in mathematics, statistics, machine learning with some knowledge of control.
  • Understanding of various machine learning algorithms and optimization methods, including (but not limited to): Support vector machine, random forests, kNN, Bayesian optimization, Evolutionary optimization, and also feature generation/transformation tools is a must.
  • Strong skills in Matlab and Python is a must (object-oriented programming and classes are a focus).
  • A good understanding and ability to identify the appropriate machine learning technique suited to achieve a desired business outcome.
  • Passion for innovation with proven problem solving skills.
  • A good understanding of statistical analysis and the methods used to validate the outcome of different machine learning algorithms.


  • A good understanding of SQL, familiarity with NoSQL is a bonus.
  • Familiarity with Python libraries like Tensoflow, or Theano, or PyTorch, and other essential tools.
  • Skills in Java and R is a bonus.


  • Development of novel mathematical models of physics/energy/power dynamics (of large-scale buildings) employing big data, machine learning and statistical modelling methods.
  • Development of robust real-time control system algorithms for automated energy efficiency optimization in a cloud-based/distributed computing environment.
  • Undertaking fundamental/enabling as well as translational R&D.
  • Prototyping, testing, validation of developed algorithms in Matlab and Python.
  • Translating R&D code into high-quality code that can run reliably within a production environment.
  • Ensuring that developed algorithms meet real-time timing/latency constraints.
  • Statistical analysis of algorithm performance as well as analysis of big data sets (power and sensor data from buildings).
  • Implementing a testing platform to enable evaluation of developed algorithms within a simulated environment.
  • Work jointly with VP of Engineering, VP of Product, and other data scientists and the larger engineering organization to contribute to all aspects of software/product modelling architecture and framework.
  • Collaborate with team leaders, and other members of the larger engineering organization to develop, enhance and document our existing and future optimization technology and platform.
  • Take a hands-on approach to actively engage and promote good software practices and methodologies to improve the quality and effectiveness of our product line.
  • Working jointly with the VP of Engineering and other members of the team to innovate and promote best practices for our modelling framework, usability and its scalability.
  • Occasional after hours technical support with operations personnel to troubleshoot critical technical modelling issues (early morning meetings with the overseas teams expected).


  • applicant must an Australian permanent resident/citizen.


Compensation and benefits will be based on experience and skills.


If you seek a growth opportunity, we encourage you to apply to Please include a cover letter that clearly demonstrates you satisfy all required skills and experience.