Key Responsibilities:

• Programming and Data Analysis:
  • Independently develop, modify, and debug programming routines (such as SAS or R) along with complex SQL queries to extract, clean, manage, and analyze large databases for health outcomes research. Data sources include medical and pharmacy claims data, hospital data, electronic medical record data, and prospective observational study data.
  • Translate study designs into algorithms to extract, analyze, and report secondary data for Non-Interventional Studies (NIS) or interactive data visualization tools.
• Collaboration and Project Design:
  • Collaborate with RWE Research Analysts to scope and design projects under senior guidance.
  • Utilize RWE tools such as R, R/shiny, SAS, Impala, git, or JIRA.
• Observational Data Analyses:
  • Conduct observational data analyses including data management and statistical programming, as well as the development of RWE dashboards.
  • Employ machine learning and data mining techniques such as random forest, GBM, logistic regression, SVM, and deep learning.
  • Utilize dimensional reduction and R packages such as ggplot, plotly, or t-sne.
• Project Documentation and Quality Review:
  • Maintain consistency and comply with company standards for project documentation, including programming, specifications of analysis datasets, tables, figures, and listings.
  • Conduct quality reviews in compliance with company standards and processes at various stages of the projects.
• Standardization and Efficiency:
  • Support and contribute to standardization techniques to increase efficiency with deliverables.
  • Ensure compliance with project timelines in collaboration with RWE Research Analysts and alert the project manager or department leadership on any risks related to deliverables and timelines.
• Customer Interaction and Presentation:
  • Interact and engage with customers on a regular basis, providing updates on project progress under senior guidance.
  • Present results, project summaries, and analytical techniques to customers, stakeholders, and internal audiences under senior guidance.

Essential Requirements:

• Educational background in a field such as computer science, bioinformatics, biostatistics, statistics or similar.
• 2+ years of experience as programmer or Scientific Data Analyst in the pharma industry, contract research organization, or academic institute.
• At least 2 years of SAS or R professional programming experience for purposes of data manipulation, analysis and visualization.
• Exceptional problem-solving abilities with a good understanding of statistical methods (regression, Anova, t-tests, etc.).
• Good knowledge of SQL querying using at least one of the following Hive, Impala, MySQL, OracleSQL or similar.

Desirable Requirements:

• Competent in using data visualization techniques such as R Shiny, Rmarkdown, ggplot, plotly, data.table, dplyr.
• Experience with version control tools such as git or JIRA.

Commitment to Diversity and Inclusion:

Novartis is committed to building an outstanding, inclusive work environment and diverse teams' representative of the patients and communities we serve.