Overview
You will be responsible for the design, development and implementation of analytical models, as well as the interpretation and presentation of statistical outcomes to support projects designed to improve patient outcomes.
You will work with healthcare providers to address their challenges through the use of data and appropriate techniques in Data Science, Optimisation and Machine Learning.
You will ensure that the solutions benefit and are adopted by users through meticulous framing/scoping of business problem, validation, execution and deployment.
You will collaborate with stakeholders to build data analytics capabilities around clinical services, conduct feasibility studies and lead research projects as required, and facilitate regular key meetings and reporting to management.
Most of all, you enjoy working with data to extract insights, and want to contribute to improving healthcare for patients.
Responsibilities
Design, development and implementation of analytical models
Interpretation and presentation of statistical outcomes to support projects
Collaborate with healthcare providers to address challenges through data science, optimisation and machine learning
Ensure solutions are adopted by users through framing, validation, execution and deployment
Collaborate with stakeholders to build data analytics capabilities around clinical services
Conduct feasibility studies and lead research projects as required
Facilitate regular key meetings and reporting to management
Job Requirements
Bachelor’s Degree in Computer Science, Mathematics, Physics, Statistics, Operations Research, Engineering or related quantitative disciplines.
Master’s Degree or PhD would be an advantage.
Preferably 1-3 years (Analyst) or 3-5 years (Senior Analyst) of hands-on experience in data science and machine learning.
Prior experience in a healthcare setting would be an advantage but is not required.
Curiosity and willingness to learn about medicine and healthcare practices are essential.
A strong understanding of the mathematical and statistical foundations of machine learning.
Fluency in Python and/or R.
Experience in several of the following skill clusters:
Data retrieval – knowledge of SQL, REST APIs
Data wrangling – expertise with pandas or similar
Data visualization and dashboards – expertise with plotly, Tableau or similar
Classical machine learning – expertise with scikit-learn or similar
Deep learning – expertise with TensorFlow and/or PyTorch
Strong problem-solving and quantitative computational ability, and strong written and oral communication skills
Ability to work with incomplete or imperfect data
Ability to work independently as well as in a team
#J-18808-Ljbffr