Data Scientist

Role Overview

The Data Scientist will partner with cross-functional teams to tackle business challenges head-on using data-driven solutions. The mission will be to build, develop, and deploy advanced AI and machine learning models. The Data Scientist will use diverse healthcare datasets to uncover actionable insights and optimize business processes.

What You Will Do

The Data Scientist will design and interpret advanced regression models, develop predictive models using machine learning techniques, and apply Bayesian and frequentist statistical frameworks to ensure robust analytical outcomes.

Why It Might Be a Fit

The Data Scientist will have the opportunity to work on a wide range of projects, from building and optimizing marketing mix models to developing next-best-action recommendation engines. The Data Scientist will also have the opportunity to work with a variety of data platforms and tools, including Snowflake and Python.

Requirements

• Master’s or PhD in Statistics, Biostatistics, Data Science, Econometrics, Applied Mathematics, or a related quantitative discipline
• 4–8+ years of relevant experience in healthcare, life sciences, or commercial analytics
• Advanced proficiency in hypothesis testing, regression analysis, ANOVA, survival analysis, Bayesian inference, experimental design, power analysis, significance testing, and small-sample statistical methodologies
• Hands-on experience developing, deploying, and validating predictive models using XGBoost, LightGBM, Random Forest, SVM, neural networks, ensemble methods, and time-series forecasting algorithms
• Expert-level proficiency in Python and SQL with experience using machine learning, statistical modelling, and explainability libraries
• Familiarity with Git, Jupyter, and CI/CD workflows
• Experience working with Snowflake, Snowpark, Spark/PySpark, MLflow, cloud-based data platforms, and scalable analytical environments
• Experience working with de-identified patient-level data including claims, specialty pharmacy, laboratory, EMR/EHR, and epidemiology datasets
• Knowledge of customer segmentation, targeting, patient identification, adherence analytics, forecasting, recommendation systems, and commercial effectiveness measurement
• Working knowledge of HIPAA requirements, explainable AI frameworks (SHAP, LIME), model monitoring, bias detection, and governance practices in regulated environments

Benefits

• Dental insurance
• Vision insurance
• Health insurance
• Retirement plan
• Paid holidays
• Flexible working hours
• Opportunities for professional development
• Collaborative and dynamic work environment
• Competitive salary and benefits package