Data Scientist (Applied AI for Estate Solutions)

What we do matters
Azendian Solutions, an AI, Data Science and Operations Technology company,develops solutions for energy and resource optimisation to achieve a smarter and more sustainable Built Environment by reducing carbon footprint, enhancing resource productivity and operations as well as lowering costs. Our AI-driven solution is game changing in its approach, leveraging on Machine Learning, Data Science, Cloud Computing with Operations Technology engineering systems.

The Role

The Data Scientist will implement cohesive data integration and analytics solutions involving both structured and unstructured data. Projects will include development of predictive, forecasting or operation research (optimisation) models as well as text mining and network analytics solutions.

Job Responsibilities

·      Work closely with clients and internal teams to understand business and operational challenges in smart building environments.

·      Lead or support client discussions to design, develop, and implement data-driven and AI-based solutions.

·      Translatereal-world problems (e.g., energy inefficiency, equipment faults) into data-driven and AI-based solutions.

·      Design and develop analytics and AI models for Anomaly detection, predictive maintenance, performance and energy optimization, etc

·      Work with real-world engineering and time-series data (e.g., equipment signals, environmental data, operational logs) including preprocessing of structured and unstructured data.

·      Develop and manage the end-to-end lifecycle of analytics projects, including problem definition and data scoping, feature engineering and modelling, deployment, monitoring, and continuous improvement.

·      Lead or contribute to small to mid-scale projects, taking ownership of delivery with appropriate guidance.

·       Proactively contribute to projects within your area of expertise and support cross-functional initiatives.

·       Define and enhance data collection processes to ensure relevant and high-quality data for analytics and AI systems.

·       Collaborate with data engineers and product teams across the full product lifecycle by concept and design, prototyping and testing, deployment and operationalisation.

·       Contribute to the development of AI-enabled features and products.

·      Present insights and recommendations clearly to both technical and non-technical stakeholders

Job Requirements

·               Bachelor’s Degree or equivalent in Computer Science, Mathematics, Statistics, Data Science, Engineering or related discipline. (Postgraduate qualifications in AI/ML are a plus but not required)

·               2–5 years of experience in data science, analytics, or applied machine-learning roles.

·               Strong foundation in the areas of programming languages (Python and SQL), data analysis and numerical computing (Pandas,NumPy/SciPy), machine-learning techniques (Scikit-learn, XGBoost or similar)

·               Strong knowledge in the areas of data science, programming languages (Python, SQL), machine learning and modelling technologies, statistical analysis, management, and strategic techniques.

·               Experience with data processing, feature engineering, and model development and working with real-world datasets (e.g.,time-series, IoT, operational data) is a plus.

·               Ability to Translate business or engineering problems into analytical and modeling approaches

·               Apply machine learning to practical use cases such as optimization, anomaly detection, or predictive analysis

·               Experience in Working with data models and writing efficient SQL queries

·               Familiar with Software engineering practices (e.g.,Git, basic CI/CD) is a plus

·               Familiar with Cloud platforms (e.g., AWS, Azure) is an advantage

·               Exposure to Smart building systems, HVAC, energy systems, or engineering domains is a strong advantage.

·               Strong problem-solving and analytical thinking skills

·               Excellent communication skills, with the ability to explain insights to non-technical stakeholders

·               Ability to work in a fast-paced environment and handle multiple projects

·               Willingness to learn and apply new technologies,including AI-assisted tools, to solve real-world problems