puestos de Machine Learning en Singapur

The candidate will be expected to perform in the following areas:

1) Developing AI-driven data products using advanced language models and Government Commercial Cloud to improve operational efficiency. For example, developing AI products to enable policy analysts to self-help in retrieving relevant data and past policy papers when designing programmes.

2) Identifying trends and insights using machine learning, advanced statistical techniques and multiple data domains such as clinical, lifestyle and genomics data to support policy and service divisions. For example, segmenting populations using multiple data domains to design targeted interventions.

3) Conducting policy simulations that integrate business rules and diverse scenarios to guide informed policy revisions.

Role and Responsibilities

1. Collaborate with stakeholders to understand needs for actionable insights.

2. Provide thought leadership to stakeholders in determining which analytics techniques and solutions will enable the enterprise to achieve defined business goals.

3. Execute both exploratory and data analysis to identify trends and data analysis to solve business problems.

4. Develop analytical models on large-scale healthcare related datasets to address various business and clinical problems through leveraging advanced statistical modelling, machine learning, deep learning, reinforcement learning and natural language processing techniques.

5. Make recommendations that aid in the realization of value and sustaining analytical activities, which seek to embed analytical tools within business processes.

6. Keep abreast of existing and emerging data science principles/theories/techniques.

7. Deliver projects in line with agreed standards, providing fit for purpose solutions within time, quality and budget constraints.

8. Develop AI/Analytics solution architectures complying with internal compliance.

9. Evaluate technologies/services, providing regular reporting on emerging trends, value add information and potential impact to the healthcare landscape.

10. Support ad-hoc engagements with business partners and stakeholders on analytics outreach activities.

Requirements / Qualifications

1. Hands-on experience in delivering AI solutions, data science or advanced analytics programme / projects, especially in designing and implementing data science or advanced analytics solutions on large datasets.

2. Good understanding of natural language processing, statistical modelling, machine learning, deep learning techniques and a track record of solving problems with these methods.

3. Master or bachelor degrees in Data Science, Computer Science, Statistics/Biostatistics/Bioinformatics, Mathematics, Operation Research, Physics or other quantitative disciplines.

4. Proficient in analytics tools such as Python or R

5. Possess good verbal and written communication, analytical and conflict resolution skills with proven ability to translate complex, technical subjects into clear and concise communications to a variety of key stakeholders of different levels (e.g. senior management)

6. Versatile in working independently as well as an effective team player.

7. The candidate will have extra advantage if he/she has experience in any of the following:

a) Prompt Engineering

b) Amazon Web Services / Microsoft Azure

c) Databricks

d) Finetuning of language models

e) Deployment of AI models

f) Big data techniques (e.g. Hadoop, Spark, Hive)

g) Public healthcare industry