Company Name:-
Novartis

Job Location:-
Hyderabad, Telangana

Job Summary:-
1 Million ! That is the number of patients datasets you get to work with every day .

We are looking for enthusiastic professionals who can Independently develop, modify and de-bug programming routines (such as SAS or R or python) along with complex SQL queries to extract, clean, manage, and analyze large databases.

Must be familiar with one of the healthcare database like healthcare claims , Electronic Medical records , Registry .

As a member of RWE team you will be conducting observational data analyses including data management and statistical programming as well as the development of RWE dashboards by translating the study design into complex algorithms in collaboration with RWE Research Analysts and colleagues or business partners across all Novartis franchises.

Job Purpose

Program and validate programming of Real World Evidence (RWE) dashboards using R and shiny.

Conduct observational database SAS programming and statistical analysis of large observational databases aligned with Novartis RWE strategies, with minimal supervision.

Your responsibilities include, but are not limited to:Lead the development of programming using languages 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.

Provide guidance and translate the study design into algorithms to extract, analyze and report secondary data for Non-Interventional Studies (NIS) or interactive data visualization tools.

Collaborate with the RWE Research Analyst to scope and design projects.

Experienced in RWE tools such as R, R/shiny, SAS, Impala, git or JIRA.

Conduct observational data analyses including data management and statistical programming as well as the development of RWE dashboards.

Experienced in machine learning and data mining techniques such as random forest, GBM, logistic regression, SVM, deep learning.

Experience in dimensional reduction and R packages such as ggplot, plotly or t-sne.

Drive consistency and compliance with company standards of the project documentation for observational studies and interactive data visualizat

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