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Search for Jobs by Ali Henderson

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Remote Data Visualization programmer (Science & Biotech)
Home Based, NC 27511
Recruited by: Ali Henderson | Recruiter | SimulStat Inc. See all my Jobs

  • Hiring Company: SimulStat's client
  • Industry: Science & Biotech
  • Compensation: Depends On Experience
  • Expires: Oct 29, 2022
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Job Description

- Long-term, remote, FSP support role:

The lead programmer position will be responsible for leading a team of programmers within our
visualization team to build applications that explore real world healthcare data assets.
Candidates must have excellent R and R Shiny programming skills and the ability to clearly communicate
project specifications to team members. Candidates must be comfortable with manipulating large
databases and be able to create complex analysis data sets derived from various data sources. Prior
experience building patient cohorts and evaluating patient healthcare events in large databases and
using observational research methods such as epidemiology and statistical methods is strongly desired.
The candidate will work within the Agile project management philosophy and will communicate with
project managers to provide work estimates for team members.
Strong communication, time management, enthusiasm and documentation skills are essential in this
home-based position.

Basic Qualifications
• Master’s degree in Epidemiology, Biostatistics, Computer Science, or other subjects with high statistical content and a minimum of 5 years relevant experience.
• Previous experience in management and/or leading a team of statistical programmers
• Proficiency with R and R Shiny

Preferred Qualifications
• Experience with real world healthcare data such as MarketScan, Optum, EMR, PharMetrics,
and/or Medicare databases
• Training or experience using the OMOP common data model
• Training or experience with SAS, Databricks, SQL, Spark SQL, or Python
• Pharmaceutical industry experience
• Experience with advanced statistical methods such as survival and regression
• Training or experience in epidemiological methods