Senior Data Scientist

Responsibilities:

• 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:
• Proficient in SQL, python, and advanced excel
• Proficient in developing ML algorithms and models at a very large scale in an industry environment
• Proficient in a range of data science algorithms (Machine Learning, Deep Learning, Reinforcement Learning, etc.). Specialisation in one field is also welcomed.
• Working experience in the MLOps process and AI governance with cloud platforms: Microsoft Azure preferred (Databricks, Synapse, Data Factory, etc.)

Preferred:

• Working experience 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
• Working experience in health outcome indices and metrics and measures
• Knowledge of patient health management, provider profiling, healthcare reporting, and other key healthcare technologies etc. is advantageous
• Knowledge of clinical tools including coders, groupers, and classifications is advantageous
• Knowledge of data science in the healthcare space is advantageous
• Knowledge of healthcare benefit pricing, product pricing and other actuarial calculations (reserving, risk rating, etc.) is advantageous

Qualifications

• Degree in either Data Science, Statistics, Applied Mathematics or Computer Science
• Masters degree plus >6 years of relevant data science experience required or bachelors plus > 8 years of relevant experience
• > 1 years of mentoring and guiding data scientist experience preferred
• Experience in healthcare data science is preferred