The Role You'll be working as a Data Scientist within an innovative health-tech company where you will apply machine learning, statistical modelling, and advanced analytics to develop data-driven solutions that improve healthcare delivery and patient care.
Develop and deploy predictive models for healthcare applications including patient risk stratification, disease progression prediction, hospital readmission analysis, clinical decision support, patient segmentation, and healthcare resource forecasting.
Design and implement feature engineering and data preprocessing workflows for clinical, operational, patient-generated, electronic health record (EHR), and time-series healthcare data.
Apply statistical techniques and machine learning algorithms to solve complex healthcare challenges, improve patient outcomes, and support evidence-based clinical and operational decision-making.
2–5+ years of experience in Data Science, Machine Learning, Advanced Analytics, or a related field.
~ Strong programming skills in Python and experience with data science libraries such as Pandas, NumPy, Scikit-learn, XGBoost, or similar.
~ Experience developing predictive models and applying statistical analysis to real-world problems.
~ Strong understanding of data preparation, feature engineering, and model evaluation methodologies.
~ Familiarity with cloud platforms such as AWS, Azure, or GCP is beneficial.
Opportunity to contribute to innovative data science and analytics solutions within a fast-growing fintech environment.
~ Strong emphasis on technical development, experimentation, and applied machine learning.
~ Clear pathways for progression into Senior Data Scientist, Lead Data Scientist, or Analytics Leadership positions.
~ Collaborative and high-performing team focused on building next-generation financial technology solutions.