Job Description
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.
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
