Associate Data Scientist

QuantHealth is an AI startup supporting drug development and clinical trials. Our ground-breaking clinical trial simulator can run thousands of trials in parallel to de-risk and optimize upcoming clinical trials. Our solution, based on a huge dataset of 350M patients and 100K drugs, drastically reduces drug development costs, shortens development timelines.

The Role: 

We are looking for an Associate Data Scientist  to join our Enrollment Prediction team. You’ll work on strategic R&D projects that directly impact customer deliverables and product capabilities. This is a rare opportunity to join a small, high-impact team where your work will influence both scientific and business outcomes. 

What You’ll Work On: 

• Assist in developing explainability tools for enrollment models, helping customers understand key drivers of recruitment. 
• Support dynamic reforecasting capabilities that update predictions as trials progress. 
• Integrate external datasets (epidemiology, regulatory, site capacity) to enrich predictions. 
• Conduct exploratory data analysis, model evaluation, and documentation. 

What We’re Looking For: 

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Life Sciences, Engineering, or a related quantitative field. 
• Strong programming skills in Python (Pandas, NumPy, Scikit-learn, Matplotlib). 
• Experience with SQL and data wrangling in large datasets. 
• Experience with version control systems such as Git.  
• Curiosity about healthcare, clinical research, or life sciences. 
• Analytical and problem-solving skills. 
• Strong communication skills and ability to work cross-functionally. 
• Bonus: background in biology, public health, epidemiology, operations research, or similar domain. 

Why Join Us: 

• Work on projects that directly shape our flagship product and customer value. 
• Learn cutting-edge techniques in predictive modeling, optimization, and healthcare data science. 
• Opportunity to grow into a specialized role in either data science or domain leadership.