Data Scientist or Advanced Analytics

Data Scientist – Advanced Analytics

Location: Remote (EST Hours)

About the Role

We are seeking a highly skilled Data Scientist with expertise in advanced analytics, machine learning, and statistical modeling to join our Pharma Analytics team. The ideal candidate will have strong hands-on experience with R, Python, and ML libraries and proven capabilities in patient-level and claims-level analytics. You will play a key role in analyzing pharma patient data to generate insights that inform market access, patient outcomes, and commercial decision-making.

Key Responsibilities

• Design, develop, and implement statistical models, machine learning algorithms, and predictive analytics solutions using R/Python.
• Conduct patient-level and claims-level analytics, including longitudinal analysis, patient journeys, adherence, persistence, and treatment pathways.
• Work with pharma datasets (IQVIA, Symphony, APLD, LAAD, claims, EHR/EMR, specialty pharmacy data) to derive actionable insights.
• Collaborate with cross-functional teams (HEOR, Market Access, Commercial, Medical Affairs) to address key business questions.
• Apply survival analysis, regression, classification, clustering, and NLP to patient-level datasets.
• Develop dashboards, visualizations, and reports for internal stakeholders and clients.
• Ensure data quality, integrity, and compliance with HIPAA, GDPR, and industry regulations.
• Stay current on pharma data science trends, advanced ML methods, and real-world evidence (RWE) analytics.

Required Skills & Qualifications

• Master’s or PhD in Statistics, Data Science, Computer Science, Biostatistics, Epidemiology, or related field.
• 5–7 years of hands-on data science experience, preferably in pharma, life sciences, or healthcare analytics.
• Strong programming skills in R or Python, including ML libraries (scikit-learn, TensorFlow, PyTorch, caret, randomForest, XGBoost, etc.).
• Expertise in patient-level and claims-level analytics
• Familiarity with pharma patient data sources (IQVIA LAAD, Symphony APLD, specialty pharmacy, claims, EMR/EHR).
• Strong statistical knowledge (hypothesis testing, regression, Bayesian methods, etc.).
• Experience working with large datasets, SQL databases, and cloud environments (AWS/Azure/GCP).
• Excellent communication skills – ability to translate complex analyses into business insights.