You will lead projects in the design, development and implementation of analytical models through strategic use of data asset for delivering efficient and effective healthcare. You will be the subject matter expert for one of the following areas: Natural Language Processing (NLP), Graph Analytics, Operation Optimization, Genomics Analytics, Blockchain for healthcare or any emerging areas that can transform the data landscape in healthcare.
You will collaborate with clinicians and end users to conceptualise solutions that address the organisation's challenges with appropriate data and techniques in Data Science, Machine Learning and Artificial Intelligence. You will drive the framing and scope of the business problem for various domains across Clinical services, Finance and Operations together with key stakeholders. You will lead the implementation of end-to-end Data and Machine Learning Operations pipeline through best practices in validation and test-driven development, continuous deployment, model monitoring and continuous re-training/integration in order to benefit and make an impact to users. You will also spearhead and conduct feasibility studies on machine learning technology stacks that will benefit and impact SingHealth, as well as facilitate regular key management meetings and reporting.
- Master's or Bachelor's Degree in Computer Science, Applied Mathematics, Statistics, Operations Research, Engineering, Data Science, Artificial Intelligence,Knowledge Engineering or related quantitative disciplines. Doctorate Degree is an advantage.
- Preferably 10 years of hands-on experience (including postgraduate research) in data mining, machine learning modelling (computer vision, natural language processing, regression, time-series etc.) and optimisation.
- Provide deep expertise and advisory in development of applications/projects using NLP methods to extract relevant data from unstructured/semi-structured dataset.
- Possess in-depth experience in applied machine learning methodology which includes Exploratory Data Analysis, data cleaning and preparation, model training and hyper parameter tuning, model selection and model deployment.
- Proficient in data science and programming languages such as Python, R, Scala, machine learning and NLP frameworks such as sklearn, tensorflow, Pytorch, spacy, HuggingFace, etc.
- Knowledgeable in SQL, Hadoop/Spark, Graph Database and related databases.
- Strong analytical and quantitative solving ability with excellent communication and leadership skills.
- Meticulous and able to work independently effectively.
- Prior experience in healthcare is an advantage.
- Must be fully vaccinated against COVID-19.