Novartis Corporation (M) Sdn Bhd is looking for new potential candidates to fill in for Real World Evidence - Scientific Data Analyst 1 (Mandarin / Japanese) position. If you currently looking for new healthcare job opportunities and qualified with the job desc, feel free to apply this job.
$9.1bn! Novartis has invested that amount in R&D, and we are committed in the clinical development and getting more patients' access for disease treatments globally.
We are hiring potential talent to fill in the role as Real World Evidence (RWE) Scientific Data Analyst who
will gain experience conducting Real World Evidence (RWE) studies (e.g. predictive health outcomes modeling) and interactive dashboards (e.g. for disease exploration) using large observational databases (e.g. medical and pharmacy claims data, electronic health records) in support of Novartis RWE strategies, improving our understanding of human diseases and improving patient health.
• Develop, modify and de-bug programming routines (such as SAS or R) along with SQL queries used to extract, clean, manage, and analyze large databases for health outcomes research under senior guidance. Data sources include medical and pharmacy claims data, hospital data, electronic medical record data, and prospective observational study data.
• Translate the study design into algorithms to extract, analyze and report secondary data for Non-Interventional Studies (NIS) or interactive data visualization tools under senior guidance.
• Gain competence with core Real World Evidence (RWE) tools such as R, R/shiny, SAS, Impala SQL, git or JIRA as well as core machine learning and data mining techniques such as random forest, GBM, logistic regression, SVM, deep learning
• Candidates must possess proficiency in either Mandarin or Japanese language.
• Minimum Master’s Degree or PhD in Computer Science, Bioinformatics, Biostatistics, Statistics or similar field.
• Basic understanding in R, SAS or another statistical programming language.
• An interest in developing programming, statistical, visualization and analytical skills.
• Exceptional problem-solving abilities with a basic understanding of statistical methods (regression, Anova, t-tests, etc.).
• Familiarity with visualization and dimensional reduction techniques, version control tools such as git or JIRA and technologies for analyzing big data.
• Open to experimentation and taking smart risks to support creative thinking that leads to practical solutions to healthcare and business challenges.
How To Apply
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