Job Detail

Job Description

As a DAE Senior Data Scientist, you will be working in a fast-paced environment that would require the ability to manage multiple priorities and needs of stakeholders, as well as the agility to respond to changes and developments. Specifically, you are expected to:
Be a technically skilled leader grounded on best practices
Be accountable for and drive assigned data science related initiatives together with a team of expert data scientists
Provide technical leadership to junior data scientists within DAE, and data scientists residing within MAS business departments
Be directly responsible for the delivery of the assigned data science products within MAS
Adhere to data science best practices, and standards for documentation, validation, and reproducibility of data science work across the team and MAS
Adhere to AI governance related policies, and ensure safe and responsible development of such products
Stay up to date on emerging data science trends, methods, and technologies
Be an effective communicator and collaborative partner
Collaborate effectively with DAE’s Production Engineering (PE) and Product Management (PM) teams to deliver enterprise grade data science products
Interface with assigned MAS business groups, and support them in identifying opportunities to deliver additional business value through data science products
Work with MAS Academy to deliver both targeted analytics training and broad-based awareness programs to all MAS staff
Promote the growth of the Data Analytics Community of Practitioners (DACoP) through organisation of workshops, training sessions, and forums to foster greater awareness of analytics within MAS
Be a supportive team player
Support any TG, DTA, DAE and/or DS Team initiatives as required
Strengthen DAE’s positive and open working norms
[What we are looking for]
Minimum bachelor’s degree in Statistics, Mathematics, Computer Science, or another quantitative field. Master or PhD degree in stated fields is a plus
10-15 years of relevant working experience developing data science products within public service and/or financial services industry independently
Deep understanding and hands-on experience in applying classification, prediction, forecasting, anomaly detection, graph analytics, deep learning, and NLP to solve business problems effectively
Ability to develop enterprise grade data science products, which typically involves frontend and backend programming on top of data science model development
Knowledge of MLOps best practices
Experience developing and deploying models and data science products on the cloud
Familiarity with various database technologies. Working experience with both structured and unstructured datasets is a must
Comfortable working on multifaceted problems in an agile environment. Demonstrate ability in overcoming business and technical constraints and deliver value adding data science products
Strong presentation and communication skills. Ability to explain technical concepts to a non-technical / business / senior management audience is a must