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Data Scientist / Statistician

Posted: October 31, 2023
Salary:US$70 - US$90 per hour
Location:United States of America
Job type: Contract
Discipline:Information Technology
Work Location:Remote

Job description

Job Title: Data Scientist / Statistician
Work Location: 100% Remote in the US
Duration: 6+ Months
Compensation: $70 - $90 / hour (Depends on Experience)

Direct talent only - please no third party subcontractor / C2C agency inquiries

Medix is currently seeking a Data Scientist / Statistician for a contract opportunity with one of our best Marketing Analytics clients

Our client conducts targeted analytics applied to a variety of marketing initiatives across the healthcare, finance, insurance and consumer goods industries. They are seeking a Statistical Modeler/ Data Scientist who has experience predicting customer behaviors using statistical and data science methods.


  • Working on end to end statistical and predictive modeling initiatives within a digital marketing space
  • Leveraging statistical methods to help segment and predict customer behaviors, and assign propensity scores for certain outcomes.
  • Conducting analysis to determine the best predictive analysis approach, using a wide variety of independent variables.
  • Planning for, and executing end to end predictive modeling projects
  • Obtaining raw data from clients, as well as from paid subscription data sources
  • Working with R, Python and PySpark to conduct data pre-processing on large data sets (hundreds of millions of rows of data)
  • Planning for, designing and building predictive models for use cases applied across the marketing industry.
  • Building and tuning a variety of multivariate predictive models, and moving them to production


  • Required Bachelor Degree in Statistics, Applied Mathematics or Data Science.
  • Masters Degree preferred
  • Minimum 5 years experience as a Statistician or Data Scientist
  • Strong statistics background with predictive modeling
  • Required 5+ years in R Studio and Python
  • Experience with Apache Spark and/or PySpark preferred