Total 2 information technology job vacancies in Maintenance / Repair category in sg ensign kallang place l7 right wing

Responsibilities:

• You will be part of the project team to assist clients in the Built Environment industry to embark on their digital transformation journey. You will be instrumental in:
• Working with stakeholders which includes client teams, industry practitioners, technology providers and research institutions to adopt latest digital technology and develop solutions to support the built environment;
• Evaluate the feasibility of the various new and emerging methodologies and technologies;
• Assist in the formulation, testing and providing recommendation to various aspects of digital transformation in project, organisation and industry-wide implementation.
• Strong familiarity and knowledge of Singapore Authorities’ regulations for buildings
• Strong familiarity with Opendata format such as Industry Foundation Classes (IFC)
• Experience of solving the technical problems faced by the project team and the problems related to the operation of the project
• Experience of guiding the project team to perform the necessary quality control tests of the created or received BIM models; Experience of checking the delivery and receipt of digital models and the coordination process with the relevant people; Strong familiarity and Knowledge of architectural and construction management practices

Requirements:

• A bachelor’s degree in architecture, Engineering, Construction Management, or a related field is generally preferred.
• Advanced degrees or certifications in BIM, project management, or related fields can enhance prospects (e.g., LEED, PMP, or specific BIM certifications).
• 7+ years of experience in BIM management or related positions, demonstrating leadership in large-scale projects.
• Extensive experience in developing BIM execution plans, setting up project standards, and ensuring compliance with industry best practices.
• Proven experience in leading BIM implementation on projects, managing BIM workflows, and collaborating with multidisciplinary teams.
• Experience in leading modelling efforts, mentoring junior modellers, and overseeing quality control of models produced by the team
• Strong interpersonal skills to facilitate collaboration between architects, engineers, contractors, and other stakeholders.
• Advanced proficiency in BIM software and tools (e.g., Autodesk Revit, Navisworks, Civil 3D, BIM 360).
• Understanding of modeling techniques, data management, and visualization tools.
• Knowledge of building codes, regulations, and standards relevant to the construction industry.
• Collating and reconciling data and information from various sources to ensure completeness and accuracy
• Good command of spoken and written English
• A keen interest in digital technology will have an added advantage.

The Team:

The DBS Investments and Trading Technologies (ITT) Data Team works with stakeholders across all pillars of the Global Financial Markets (GFM) Department to create proprietary algorithms and data science solutions for trading, sales, and operations.

We are seeking a machine learning specialist who thrives in dynamic environments, possesses a strong foundation in data science and a keen interest in leveraging data to drive innovation in the financial markets and banking sector.

Responsibilities:

1. Utilize extensive financial datasets to drive end-to-end data science solutions for algorithmic pricing, experiment design, process optimization, and customer hyper-personalization.
2. Work with quants, traders, and dealers to solve complex optimization problems using advanced machine learning and quantitative methods.
3. Conduct research and literature reviews to assess quantitative algorithms and models, ensuring the adoption of optimal methodologies.
4. Implement and train AI/ML models, optimizing algorithm and system efficiency through GPU distributed computing and concurrent programming.
5. Create reusable libraries/ microservices, deploy machine learning ecosystems, and integrate subsystems as necessary.

Required Experience:

1. Bachelor's degree or higher in a quantitative discipline, such as Mathematics/Statistics, Quantitative Finance, Computer Science, Engineering, or equivalent experience.
2. Proficient in the data science project life cycle, demonstrated by a proven track record of working with structured, semi-structured, and unstructured data.
3. Deep understanding and application of various machine learning concepts, their mathematical underpinnings, and trade-offs.
4. Exceptional programming skills in Python (Or demonstrable ability to pick up new languages) and SQL variants, with knowledge of design patterns, code optimization, and object-oriented design.
5. Familiarity with software development best practices and tools such as Agile methodologies, Jira, Jenkins, and Git.

Good to have (Two or more):

1. Familiar with Linux OS, Openshift, Kubernetes for container-based deployment.
2. Demonstrable expertise in econometrics, statistical modelling, time-series analysis, causal inference, and their applications to pricing and marketing domains.
3. Hands-on experience in designing and executing digital experimentation and hypothesis testing, including A/B testing, bandit-based experiments, and multivariate analysis.
4. Experience with language models, RAG concepts, opensource generative AI (GenAI) frameworks and prompt engineering principles.
5. Experience with machine learning applications in financial markets with a solid understanding of market dynamics, and key drivers.
6. Experience developing reinforcement learning models and frameworks at scale.
7. Strong research background with experience conducting literature reviews and prototyping fit-for-purpose custom models.
8. Experience building scalable machine learning system architectures (microservice, distributed, etc.) and big-data pipelines in production.

Key Skills: python, algorithms & data structures, machine learning, causal inference, SQL, experimentation, A/B Testing, multi-armed bandit, pricing, econometrics, software design, time-series analysis, research, financial markets, behavioral science, quantitative analysis, RAG, large language models.

Internal Description

Description - Internal

The Team:

The DBS Investments and Trading Technologies (ITT) Data Team works with stakeholders across all pillars of the Global Financial Markets (GFM) Department to create proprietary algorithms and data science solutions for trading, sales, and operations.

We are seeking a machine learning specialist who thrives in dynamic environments, possesses a strong foundation in data science and a keen interest in leveraging data to drive innovation in the financial markets and banking sector.

Responsibilities:

1. Utilize extensive financial datasets to drive end-to-end data science solutions for algorithmic pricing, experiment design, process optimization, and customer hyper-personalization.
2. Work with quants, traders, and dealers to solve complex optimization problems using advanced machine learning and quantitative methods.
3. Conduct research and literature reviews to assess quantitative algorithms and models, ensuring the adoption of optimal methodologies.
4. Implement and train AI/ML models, optimizing algorithm and system efficiency through GPU distributed computing and concurrent programming.
5. Create reusable libraries/ microservices, deploy machine learning ecosystems, and integrate subsystems as necessary.

Required Experience:

1. Bachelor's degree or higher in a quantitative discipline, such as Mathematics/Statistics, Quantitative Finance, Computer Science, Engineering, or equivalent experience.
2. Proficient in the data science project life cycle, demonstrated by a proven track record of working with structured, semi-structured, and unstructured data.
3. Deep understanding and application of various machine learning concepts, their mathematical underpinnings, and trade-offs.
4. Exceptional programming skills in Python (Or demonstrable ability to pick up new languages) and SQL variants, with knowledge of design patterns, code optimization, and object-oriented design.
5. Familiarity with software development best practices and tools such as Agile methodologies, Jira, Jenkins, and Git.

Good to have (Two or more):

1. Familiar with Linux OS, Openshift, Kubernetes for container-based deployment.
2. Demonstrable expertise in econometrics, statistical modelling, time-series analysis, causal inference, and their applications to pricing and marketing domains.
3. Hands-on experience in designing and executing digital experimentation and hypothesis testing, including A/B testing, bandit-based experiments, and multivariate analysis.
4. Experience with language models, RAG concepts, opensource generative AI (GenAI) frameworks and prompt engineering principles.
5. Experience with machine learning applications in financial markets with a solid understanding of market dynamics, and key drivers.
6. Experience developing reinforcement learning models and frameworks at scale.
7. Strong research background with experience conducting literature reviews and prototyping fit-for-purpose custom models.
8. Experience building scalable machine learning system architectures (microservice, distributed, etc.) and big-data pipelines in production.

Key Skills: python, algorithms & data structures, machine learning, causal inference, SQL, experimentation, A/B Testing, multi-armed bandit, pricing, econometrics, software design, time-series analysis, research, financial markets, behavioral science, quantitative analysis, RAG, large language models.