Analyst – Data Scientist

Role Overview

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

What You Will Do

Develop, validate, and deploy predictive models using machine learning techniques, build survival and time-to-event models, design experimental and quasi-experimental studies, and develop forecasting solutions.

Why It Might Be a Fit

You will be part of a team that values diversity of thought as much as diversity of people. We believe in empowering our employees through tailored development programs that align personal growth with our mission.

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
• 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 time off
• Flexible work arrangements
• Professional development opportunities
• Diverse and inclusive work environment