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Model Automation Engineer (JHB)

IT – Software Testing
Johannesburg – Gauteng

ENVIRONMENT:
DO you install R, Python, Anaconda, Docker and other open-source tools for kicks? Do you like seeing if you can connect to data sources and make the data available to those that can really extract value from it? Then a fast-paced Analytics Consultancy in Joburg wants you as its next Model Automation Engineer. You must have a Bachelor’s Degree in an IT-related field, ±2 Years’ experience in using Python and similar open-source tools and practical projects in Python and you need to be comfortable living in a Unix shell.
 
DUTIES:
  • Ensure Data Science environments are set up for quants.
  • Assist quants with connecting to clients’ data sources, including understanding proxies and ssh tunnelling.
  • Setup cloud environments for quants to practice modelling.
  • Setup version control and best practice environments for data scientists (for an example, look at the Data Science Cookiecutter).
  • Assist quants with understanding on best practices for version control, testing and setting up environments.
  • Some ad hoc data science requests such as automating extracts and web scraping.
  • Look after various cloud setups for the business and clients.
  • The company will assist you by paying for online courses, but the candidate will be expected to complete the courses in their spare time.
 
REQUIREMENTS:
Qualifications –
  • Minimum of a Bachelors’ Degree in an IT related discipline.
  • Ideal: some Coursera / similar qualifications.
  • Bonus: Honours or Masters’ level qualification.
 
Experience/Skills –
  • ±2 Years’ experience in using Python and similar open-source tools.
  • Practical experience in Programming.
  • You need to be comfortable living in Unix shell.
  • Practical projects with Python are a must.
  • Consulting experience would be advantageous.
 
The tech you will be exposed to will be a myriad of environments, tools and languages. It is very likely that you will get exposure to:
  • Excel
  • R
  • Python
  • SAS
  • Docker
  • Kubernetes
  • Serverless environments (primarily on GCP, but likely on other cloud environments)
  • Snowflake
  • Spark / Hadoop / Kafka / Cloudera Stack
  • Anaconda