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