With Python on your resume, you may end up with one of the following positions in a reputed company🔥:


  • Software Engineer – $103,035/yr
  • Sr. Software Engineer – $129,328/yr
  • DevOps Engineer – $115,666/yr
  • Data Scientist – $117,345/yr
  • Sr. Data Scientist – $136,633/yr
  • Python Developer -- $122,093/yr
  • Product Manager -- $187,000/yr
  • Data Analyst - $100,000/yr

1. Software Engineer

  • Analyze user requirements
  • Write and test code
  • Write operational documentation
  • Consult clients and work closely with other staff
  • Develop existing programs

2. Senior Software Engineer

  • Develop high-quality software architecture
  • Automate tasks via scripting and other tools
  • Review and debug code
  • Perform validation and verification testing
  • Implement version control and design patterns

3. DevOps Engineer

  • Deploy updates and fixes
  • Analyze and resolve technical issues
  • Design procedures for maintenance and troubleshooting
  • Develop scripts to automate visualization
  • Deliver Level 2 technical support

4. Data Scientist

  • Identify data sources and automate the collection
  • Preprocess data & analyze it to discover trends
  • Design predictive models and ML algorithms
  • Perform data visualization
  • Propose solutions to business challenges

5. Senior Data Scientist

  • Supervise junior data analysts
  • Build analytical tools to generate insight, discover patterns, and predict behavior
  • Implement ML and statistics-based algorithms
  • Propose ideas for leveraging possessed data
  • Communicate findings to business partners

6. Python Developer

  • Build websites
  • Optimize data algorithms
  • Solve data analytics problems
  • Implementing security and data protection
  • Writing reusable, testable and efficient code

7. Product Manager

  • Responsible for researching new user features
  • Find gaps in the market
  • Make an argument for why certain products should be built.

8. Data Analyst

  • Designing and maintaining data systems and databases
  • Mining data from primary and secondary sources
  • Using statistical tools to interpret data sets


Thank You!

Happy Learning😊