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Medical Actuary/statistician Resume

Plantation, FloridA

SUMMARY:

A problem solver computational mathematician - statistician, knowledgeable, trained and with years of experience in applied mathematics. Successful in coding much software, some from scratch, fixed others, in different (symbolic) languages and platforms. Derived models, simulated their properties, compared them with others and validated them with experimental data.

TECHNICAL SKILLS:

  • Trilingual (English, Spanish, Swedish).R (RStudio, knitr, Markdown)
  • SQL
  • SAS
  • Python
  • MS Office 365
  • Matlab
  • Maple
  • Mathematica
  • C/C++
  • MPI parallel
  • LATEX
  • Linux/Unix System
  • High-performance computing clusters
  • Computational Flows

EXPERIENCE:

Confidential, Plantation, Florida

Medical Actuary/Statistician

Responsibilities:

  • Medical cost and savings in-depth analysis with hands-on experience in health insurance data and other patients' and physicians' data sources.
  • Determine which physicians were too expensive to health plans for repeatedly not choosing the correct treatments, based on cost effectiveness analysis.
  • Make recommendations and reporting.
  • Introduced statistical methods, e.g. standard testing, Bayesian, clustering, elements of Confidential, training-based learners, etc, for but not limited to, detect missing terms, actuarial calculations, trends, outliers.
  • Proposed and implemented a methodology for data-based extraction of Confidential values, for cost effectiveness analysis.
  • Initiated causal inference and counterfactual to further analyze patients' and physicians' behavior.

Confidential

Applied Mathematician/ Researcher

Responsibilities:

  • Advanced probabilistic and statistical analysis, both theoretical and based on data.
  • Use data from external contractors to do probabilistic and statistical analysis.
  • Sole author of a new probability based moment system, and its corresponding discrete distribution function, which is mathematically more general than an existing one, dated from Confidential century.
  • This solved a many decades old problem, linked to the tail of the distributions.
  • Implemented risk analysis in data, to detect which groups were more likely to relapse.

Confidential

Researcher

Responsibilities:

  • Probabilistic based analysis and calculation, theoretical and validation with experimental data.
  • Proposed and numerically implemented a cheap computationally feasible methodology, which matches a multimillion-dollar experiment.
  • Comparison of some methods to determine which one was the best one, based on computational cost, accuracy, etc, which has been part of a dispute (Publication 4 ).

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