Also avaliable as a pdf, last updated 8/4/20.

Email: petra <dõtté> lamborn [ât] petras <dõtté> space
Website: petras.space
Git: git.petras.space/petra and github.com/PetraOleum
LinkedIn: www.linkedin.com/in/petra-lamborn-19a486153

Summary

I’m a passionate early-career statistician/data scientist and analyst. My language of choice is R, along with Python, and with bash and C++ for non data-related tasks. I’m also skilled with a variety of other tools such as git and QGIS.

Skills and Experience

  • Statistical estimation, modelling, and prediction
  • A broad base of knowledge, particularly including biology and higher mathematics
  • Problem solving and critical thinking
  • Programming in R (including the tidyverse and RShiny), Python, SQL, and C++
  • Report writing and automatic generation
  • GIS tools such as ArcGIS and QGIS
  • Microsoft Office, including Excel
  • Linux administration, including AWS EC2, DigitalOcean droplets, and Linode
  • Version control with git and Objective
  • Data entry and data cleaning: speed, reliability, and patience
  • Real-world experience including building a statistical model for a startup
  • Experience with substantial team and solo projects

Education

  • Masters of Applied Statistics at Victoria University of Wellington (2018-2019)
    • Achieved with merit
  • GDipSc in Statistics at Victoria University of Wellington (2017)
  • BSc at Victoria University of Wellington (2013-16)
    • Major: Cell and Molecular Bioscience
    • Minor: Mathematics

Selected course marks

  • Bayesian Statistics: A
  • Computability and Complexity: A+
  • Computational Statistics: A-
  • Data Management and Programming: A+
  • Statistical Consulting: A
  • Generalised Linear Models: A+

Work History

  • Data System Analyst, Statistics New Zealand (May 2021-Present)
    • International Trade team
  • Administration Assistant, RNZCGP (March 2021)
    • Quantitative and Qualitative analysis
  • Data entry administration, RNZCGP (February-March 2020)
    • Discovered multiple process improvements for speed and accuracy
  • Undergraduate statistics marker, VUW (2019)
    • STAT 193 and STAT 292
    • Fast turnaround with high accuracy
  • Intern, Ampli (Jan/Feb 2019)
    • AWS EC2
    • Postgresql
    • Electricity demand modelling and prediction with R and Python
  • Volunteer, Lower Hutt Foodbank (2017-18)
    • Sorting, lifting, etc
  • Data entry, Comparative Education Research Unit, Ministry of Education (summer 2014-15 and 2015-16)
    • Data cleaning
    • TIMMS, TALIS, and related education surveys
  • Volunteer, Trade Aid Petone (2013-14)
    • Stocktake
    • Invoices
    • Tech support
    • Backroom work