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Data Scientist or Advanced AnalyticsJConnect Infotech • United States
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Data Scientist or Advanced Analytics

JConnect Infotech
  • US
    United States
  • US
    United States
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À propos

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.
  • United States

Compétences linguistiques

  • English
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