Job Description

[What the role is]

The HDB Data Science and Artificial Intelligence Centre of Excellence (DSAI COE) sets the standards of excellence for artificial intelligence at the agency. Our team comprises of experienced data science practitioners tasked with solving the most challenging business problems of the agency. By joining us, you will be part of a dynamic team that's always learning and always challenging ourselves to do our best for the public good.

[What you will be working on]

• Contribute to data science strategy as a core member of the DSAI COE. Specifically, you support the team's transition towards industry standard MLOps frameworks, support the DSAI COE's core efforts to provide value returns to HDB's business units, and aid the elevating of skills and talent within the DSAI COE and across our agency.
• Take on the most challenging and strategic data science projects undertaken by the COE. You will lead the management of project teams, engage in high impact problem-solving exercise, engage in the selection and implementation of algorithms, and be responsible for the accuracy, efficiency, explainability, and integrity of your team's solutions.
• Provide technical guidance and mentorship support for the data scientists attached under you. You will be responsible for organizing their efforts, uplifting their core competencies, and reviewing their work to ensure high standards and conformity to best practice.
• Engage key stakeholders from IT and business units to co-create high impact and high value solutions for HDB. This involves frequent engagement and maintenance of favourable relations with the stakeholders.
• Stay at the cutting edge of data science innovations by actively surveying the DSAI landscape and consistently uplifting your technical proficiency.

[What we are looking for]

• 10 years of hands-on data science work with at least 3 years of leading data science project teams.
• Masters in Computer Science / Data Science / Artificial Intelligence / Operations Research
• High proficiency in problem-solving for data science (e.g. with suitable frameworks like MECE, root cause analysis, etc.).
• High proficiency in MLOps as a framework, with strong experience in end-to-end model development and deployment in the cloud (e.g. AWS).
• Seasoned in the theory and execution of deep learning algorithms and architectures (e.g., transformer models, reinforcement learning), AI Engineering (e.g., neural embeddings, LLM models, building of GenAI systems with frameworks like LangChain and LangGraph, strong understanding of vector databases, EDD, etc.), optimization, statistical modelling, and multi-criteria decision analysis.
• Experience with data engineering for data science (e.g., ELT concepts, structured table transformation experience, database technologies, etc)
• Superb communication and visualization abilities.
• Advanced programming and development skills in python (and accompanying frameworks), R, SQL, shell languages