Python Consutant

Company: Pionear Recruiting
Location: Not Specified, Not Specified, United States
Type: Full-time
Posted: 02.SEP.2021
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Summary

This role is centered around the application of Python and its flexibility across imperative, object-oriented, and functional programming st...

Description

This role is centered around the application of Python and its flexibility across imperative, object-oriented, and functional programming styles. It includes building reusable assets in a Pythonic environment and embodies core principles of The Zen of Python. While an early focus of the role will be on designing and building the model development and execution patterns of the future, there will remain a consistent and ultimately primary intent to establish, educate, and evangelize the best practices required of data scientists to successfully use these platforms with robust and resilient code. The role requires a willingness to teach these principles to other members on the team.
In This Role You Will

  • Own in-house developed tools & libraries in support of statistical and machine learning model building and deployment to various execution platforms including:
    • New tool and platform discovery and investigation
    • Technical documentation in support of playbook(s) standards, FAQs
    • Tool adoption, modification, and development to standardize, automate and inner-source best practices for data source access, model development, model promotion to production and model monitoring
  • Leverage expertise on platforms and software best practices to enable and improve data scientists' code resiliency and performance including:
    • Developing or curating training for software development best practices for data scientist mastery on model build and execution platforms
    • Developing code and repo quality standards and train data scientists to adopt and adhere to these standards with structured peer code reviews
    • Host office hours or other avenues to assist data scientists in need of assistance on model build and execution platforms and tools
    • Engage with the data science community to solicit feedback and lead virtual or in-person training sessions
    • Develop and maintain up to date playbooks for the tools and development practices
  • Performance optimization: evaluate existing ML pipelines and analyze computational optimizations using the latest in distributed storage and compute paradigms.

Basic Qualifications

  • Bachelor's Degree plus 6 years of experience in data analytics, or Master's Degree plus 4 years in data analytics, or PhD plus 1 year of experience in data analytics
  • At least 2 years of experience in open source programming languages for large scale data analysis
  • At least 2 years of experience with machine learning
  • At least 2 years of experience with relational databases

Preferred Qualifications

  • Bachelor's Degree or Master's Degree in Computer Science, Computer Engineering, Statistics, Math plus 3 years of experience in data analytics
  • At least 1 year of experience and proficiency in working with AWS (S3, EMR, EC2, IAM, Lambda)
  • At least 2 years of experience with containerization (Docker)
  • At least 4 years of experience working in Python
  • At least 4 years of experience with PyData software stacks (pandas, numpy, scipy, sklearn, statsmodels)
  • At least 4 years of experience with machine learning
  • At least 4 years of experience with SQL
- provided by Dice

 
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