Head of Data Science & ML Engineering

About Us

NE Digital is the digital, data and technology organization that serve as a center of excellence to drive digital transformation for our group of NTUC Social Enterprises to meet the critical social needs of Singapore's community. Delivering innovative products and solutions, we empower our people to lead a better and meaningful life through digital services in the area of daily essentials, health and community care, childcare and education as well as financial services.

The Team

We believe that diversity is key to driving an innovative, cohesive, productive and fun workplace! Hence, at NE Digital our people join us from all around the world. Be sure to be soaked in an environment with different ethnic groups driving innovation and injecting some creative juice as one!

Contributing to a social purpose through technology, our team of passionate and dedicated folks are spread into different social enterprises such as NTUC FairPrice Group, NTUC First Campus, NTUC Health and among others!

Job Description

The role of Head of Data Science & ML Engineering is responsible to lead the teams of data science & ML engineering. With a deep understanding of the business, this role will define and drive the overall strategy and execution of data science & ML engineering at a group level to drive the adoption of AI/machine learning solutions to solve critical business problems for the FairPrice Group as well as other Social Enterprise(s). You will lead the DS and MLE team to own and operate the group-wise AI/ML infrastructure and support analytics across the group. This role will also work with BU analytics teams to discover data-driven opportunities to improve business (revenue growth/cost reduction/operation).

The successful candidate will develop advanced analytics capabilities and execute an enterprise data warehouse strategy, execution, and maintenance across social enterprises within a central group analytics office capability.

You will be reporting to the Chief Data Officer.

As we embark on the journey of data-driven analytics & AI transformation, this senior role will lead and drive the journey of data science and machine learning. The role needs to cover but not be limited to the following responsibilities:

• Drive the creation and prioritization of the DS & ML engineering roadmap with a clear estimation of business impact/values;
• Lead the data science team to build effective machine learning/AI solutions and to deploy to the production environment to solve real-world business problems (both external customer facing applications as well as internal facing operations).
• Iterate the experiment of A/B testing and optimize/refine the predictive models;
• Effectively work with stakeholders to drive the execution of analytics projects including identifying, acquiring, synthesizing, and analyzing relevant data.
• Prepare and review written analyses, reports, presentations, and interrogatories for third parties on the project scope and/or results of activities.
• Drive the data-driven culture across multiple NTUC SE business departments to transform the organization to be data-driven.

Requirements

• Experience in driving data science & AI strategy and roadmap.
• Knowledgeable in machine learning, operation research, statistical inference etc. and experienced in real-life application of data science & machine learning.
• Highly experienced in managing and operating cloud-based AI/ML infrastructures and MLOps lifecycle management.
• Worked closely with business stakeholders, analytics teams, and product teams to formulate data science/machine learning problems, develop and deploy advanced machine learning algorithms, and conduct solid A/B testing.
• Managed budgets and drive financial discipline to achieve positive business outcomes in a profitable manner.
• Demonstrated experience in strong presentation skills, communication and articulation to a diverse group of stakeholders ranging from business operations to executives.
• Experience in building, managing and growing DS/ML engineering teams.