Do meaningful work with us. Every day.
At Amplify Health, we're looking for individuals with ambition, resilience and passion for healthcare, insurance, wellness and digital technology. As a fast-growing business with the ambition of making people and communities across Asia healthier, we have exciting career opportunities available to help us achieve our vision.
The primary objective of the role is to ensure timeous, robust and accurate delivery of relevant data science methods including responsibility of research, development, and monitoring of models. The role will work with cross functional teams across data analytics, actuarial analytics, data science, clinical (coders and doctors), and data engineers in an international team. Effective communication between a range of stakeholders is vital to ensure delivery.
The ideal person has a passion for data and understand the life journey of data. Core responsibilities include:
What skills do you need? Behavioural skills
- Connecting with a multitude of local and international stakeholders to understand the data, systems, and analytical processes in a healthcare context
- Develop data science models fit for purpose to solve business problems
- Research and application of new data science techniques fit for purpose to solve real world problems
- Rapidly test and iterate different data science algorithms
- O wn model monitoring statistics and trigger points to decide model retraining parameters.
- Work with the ML Engineers to deploy ML models successfully and enable monitoring of the model performance
- Mining large structured and unstructured datasets for a multitude of companies with different data structures
- Usage of data science to find new insights to inform healthcare strategies and develop product - there will be a broad range of products to understand from clinical, operations, financial, fraud , digital, sales and marketing, wellness, etc.
- Performing basic ad hoc data analytics to extract core data insights
- Present data and model findings in a way that provides actionable insights
- Improve processes and data outcomes where opportunities arise
- C ommunication skills across a wide range of stakeholders
- Ability to work cohesively in a team environment with key focus on the data
- High level of attention to detail, resilience, enthusiasm, energy and drive
- Positive, can-do attitude focused on continuous improvement
- Ability to take and provide feedback to drive improved delivery
- Rigorous ability to problem - solve and optimise environment
A working understanding of the data used in healthcare is optimal as data forms the basis of products, as such the following core understandings are required:
- Experience using SQL, python, and advanced exce l for performing exploratory data analysis for data science projects
- Experience in a range of data science algorithms (Machine Learning, Deep Learning, Reinforcement Learning, etc.).
- E xperience of building & deploying machine learning models in cloud environment : Microsoft Azure preferred (Databricks, Synapse, Data Factory, etc.)
- K nowledge of the MLOps process and AI governance
- Knowledge of the model lifecycle in at least 2 out of the following areas of expertise from clinical, operations, financial, fraud, digital, sales and marketing, wellness, or any relevant dataset in healthcare
- Knowledge of health outcome indices and metrics and measures
- Knowledge of patient health management, provider profiling, healthcare reporting, and other key healthcare technologies etc. is advantageous
- K nowledge of clinical tools including coders, groupers, and classifications is advantageous
- Knowledge of data science in the healthcare space is advantageous
- Knowledge of h ealthcare benefit pricing, product pricing and other actuarial calculations (reserving, risk rating, etc.) is advantageous
- Degree in either Data Science, Statistics, Applied Mathematics or Computer Science
- Master's degree plus 1 to 5 years of relevant data science experience required or bachelors plus 1 to 7 years of relevant experience required
- Experience in healthcare data science is preferred.
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