Join us as we support Singapore’s vision of building a Smart Nation - a nation of possibilities empowered through info-communications technology and related engineering.
The Data Science & Artificial Intelligence Division (DSAID) works with public sector agencies in using data science and AI to improve policy outcomes, service delivery and operational efficiency. We extract data-driven insights and build intelligent platforms to add value to the work of our partner agencies. We also help public sector agencies transform by partnering them in building data science expertise, formulating data strategies and setting up the necessary data infrastructure.
How Do We Work
Outcome Driven - Our projects are not academic exercises. We are driven by the “so what” and make sure that our findings and models can be translated into tangible impact.
Start Small and Move Fast - We build things quickly. If it works, good — how can we scale this up further? If not, what went wrong and what can we do better next time?
Ownership - You are not just here to write code, but also to figure out what we should be building and how we should build it.
Continuous Learning - Working on new ideas often means not fully understanding what you are working on. Taking time to learn new architectures, frameworks, technologies, and even languages are not just encouraged but essential.
We are in this Together - We draw from the deep domain knowledge of our partners and best practices from our community of experts.
Read more about us from the team's blog https://medium.com/dsaid-govtech
As an Agency Data Science Team Lead, you will set up and lead a data science team in a government agency, to drive the growth of data science capabilities at the partner agency while operating in close alignment to DSAID’s approach and philosophy.
You will guide the team to work closely with the multiple business stakeholders at the partner agency to proliferate data-driven decision making at the partner agency. This include identifying and executing a pipeline of impactful data science projects, proposing improvements to the agency’s data management practices and analytics infrastructure. Where necessary, you will also help the team in overcoming project blockers, by working with partner agency’s IT teams on the setup of relevant tools, systems and infrastructures needed for project development and deployment.
This role requires an individual with strong stakeholder management and communication skills, as it involves identifying and building relationships with strategic partners in the agency. You will also be reporting to multiple stakeholders, both at GovTech and the partner agency. To ensure that the team operates in close alignment with DSAID’s approach and philosophy, you and your team will meet up regularly with the central DSAID team and other agency data science teams, to exchange learning points and best practices across agencies.
Individuals with strong stakeholder management, problem solving and project management skills, as well as the ability to lead a team to deliver sound and robust data science solutions are welcome to apply.
What To Expect
You will be involved in a range of tasks including the following:
- Manage a team of 2-3 data scientists and data engineers deployed to the agencies that we partner with, to drive the growth of data science capabilities at the partner agency that you are deployed to.
- Work closely with business stakeholders at the partner agency to build a strong pipeline of impactful projects. This will involve understanding their business challenges, scoping the problem and developing business cases on how to turn data into critical information and knowledge which can then translate into action and impact.
- Organise and guide the team to execute the pipeline of projects by performing data cleaning, pre-processing, and feature engineering to build relevant models to conduct meaningful analysis. Iterate with key stakeholders to perform subsequent deep dives based on initial insights. Depending on the use case, design dashboards and interactive visualisations as tools for data exploration and storytelling.
- Work with the agency Chief Data Officer (CDO)’s and Chief Information Officer (CIO)’s Offices to improve the agency’s data management and analytics infrastructure, and to grow data science capabilities within the agency’s workforce.
- Support the professional growth and development of the data scientists and data engineers in your team and forge a positive team culture to ensure staff retention
How To Succeed
- A Bachelor’s Degree or in Computer Science, Statistics, Economics, Quantitative Social Science, or related discipline. Advanced degrees are preferred. Relevant training and certifications (e.g. Coursera) may also be considered.
- At least 5 years of relevant experience, in data science and/or the public sector, preferably with experience managing a team.
- Have strong analytical, conceptualisation and problem-solving skills. Able to take broad, strategic perspectives, and when necessary, drill deep to understand business needs and challenges.
- Understand key concepts, techniques and considerations in statistics, machine learning and data analytics.
- Training and relevant experience in one or more of the following areas:
- Data science tools such as R, Python
- Visual analytics technologies like Tableau, Qlik
- Demonstrable experience in project management of technical initiatives
- Have excellent oral and written communication skills, along with the ability to pitch ideas and influence stakeholders at all levels on the adoption of analytics. Able to present technical concepts and results of technical analyses to non-technical audience in a concise manner.
- Adaptable to dynamic operating contexts and able to work with multiple stakeholders across different teams and agencies
- Strong people manager who can inspire, motivate and grow the team and has strong organisation skills. Effective in setting and managing individual and team KPIs
- Have passion for improving public service through the use of analytics and data.
- Experience in model deployment with skillsets in ML Ops, DevOps or software engineering
- Knowledge in data management, data warehousing, data engineering
- Experience in agile project management
- Experience in developing capability in others
- Understanding of processes in digital transformation