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Urban Redevelopment Authority

Systems Analyst (AI Engineer)

Urban Redevelopment Authority

Permanent/Contract

What the role is

About Urban Redevelopment Authority (URA) The Urban Redevelopment Authority (URA) is Singapore’s planning authority. Our mission is to make Singapore a great city to live, work and play. We plan and facilitate the physical development of Singapore, in partnership with agencies and the community, to create a vibrant, sustainable and cosmopolitan city of distinction. URA has undergone a digitalisation journey to harness Geospatial and Data Analytics for more data-informed planning. URA was recognized as the Asia Pacific 2017 regional DX Leader in Talent Acceleration by IDC and received the 2019 Business Transformation Award from PSD. URA has embarked on a Digitalization 2.0 effort to progress from planning analytics, to strengthening the use of Modelling and Simulation, as well as AI technologies, in urban planning and design. URA is also the Whole-of-Government “Urban Planning & Design Technology Centre of Excellence” (URBEX), and will play the role to digitalise and cohere the urban planning and design ecosystem in its use of data, tools and models. About Design and Planning Lab Be part of the URA Design and Planning Lab, which spearheads development and experimentation of smart planning technologies through Ops-Tech collaborations. Our teams, with capabilities in data management, engineering and governance, software development, urban design technologies, data science, modelling and simulation, work closely with planners, architects and policy makers across various agencies to generate insights and develop digital solutions to tackle interesting challenges of Singapore’s urban planning needs.

What you will be working on

You will partner business leads and management to lead initiatives and teams in building Artificial Intelligence (AI) solutions for the Urban Planning & Design domain. You will serve as the subject matter expert in the application of machine learning and natural language processing techniques in knowledge-based systems, to equip URA’s planning processes with AI decision support systems, that strengthen URA’s ability to meet the needs of a changing operating environment. You will work collaboratively with internal user groups (Urban Planners, Architects, Data Engineers, Data Scientists, Software Developers, etc.) in the scoping, architecting, development, deployment and integration of machine learning or AI solutions using cloud or on-premise infrastructure, as well as training team members and the URA community in the use of AI technologies. You will build performant infrastructure and pipelines and set up Machine Learning Ops (“MLOps”) for our teams to rapidly deploy and productionise their work. You will also collaborate with other WOG agencies, academic and industry partners to harness external expertise to inform and address capability gaps, as well as foster an AI Urban Planning eco-system. You will need to present to URA senior management and update key partner agencies on the progress of URA’s AI efforts, and explain complex technical information and analysis in a manner where the key principles, concepts and implications are easy for a general audience to understand. You will also engage WOG agencies on our AI efforts, to identify synergies and opportunities for potential collaborations.

What we are looking for

Requirements: ● Have a keen interest in cities and in applying expert knowledge and expertise to develop AI/ML-enabled solutions that will enable Urban Planners to make Singapore an even more liveable, sustainable and economically competitive city. ● Bachelor's Degree or higher in Computer Science, Data Science, or related disciplines. We will also factor in relevant certifications (e.g., Coursera). ● At least 2 years of relevant experience, in machine learning engineering, data science, data engineering, or other data-heavy roles, and proficiency in the following: o Common machine learning algorithms and key parameters, Natural Language Processing, Knowledge-based Systems (KBS) and Generative AI projects. o Developing and optimising machine learning or AI models using common Python packages such as scikit-learn, TensorFlow, or PyTorch. o SQL and/or NOSQL databases technologies such as MSSQL, MongoDB o Working with cloud infrastructure and services to deploy machine learning models, pipelines, or solutions (e.g. Microsoft Azure/AWS) o Containerization technologies such as Docker and orchestration platforms like Kubernetes, with a strong understanding of deploying and managing machine learning models in containerized environments. o Capable of architecting machine learning or AI solutions that meet the users’ needs while being effective, reliable, secure, scalable, and cost-efficient. o Capable of cleaning, imputing, and correcting anomalies in the collected structured or unstructured data to ensure high data quality standards. o Capable of Machine Learning Operations framework (mlflow, Kubeflow) and building model monitoring solutions and processes to check for model, concept, and data drifts ● Ability to work well in cross-functional and interdisciplinary teams, e.g with engineers and data scientists in development and training of ML models. ● Is keen to learn and share new methods and techniques with team members ● Good communication and inter-personal skills Preferences: ● Understanding or experience in machine learning or AI governance, especially in explainability and fairness. ● Experience in delivery of machine learning or AI solutions for internal teams or external clients

About Urban Redevelopment Authority

The Urban Redevelopment Authority (URA) is Singapore's national land use planning authority. URA prepares long term strategic plans, as well as detailed local area plans, for physical development, and then co-ordinates and guides efforts to bring these plans to reality. Prudent land use planning has enabled Singapore to enjoy strong economic growth and social cohesion, and ensures that sufficient land is safeguarded to support continued economic progress and future development.