The best Python jobs to watch out for

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Python is one of the most popular programming languages ​​in the world and it also offers the most promising career opportunities. This demand for Python developers is increasing every year. There is a reason why this high level programming language is so popular. The python language is one of the most accessible programming languages ​​available because it has a simplified syntax and is not complicated, which puts more emphasis on natural language. Python is also one of the best tools for creating dynamic scripts on both large and small scales. This article lists the best Python jobs for 2021.

Python Developer

The most suitable job that you need to do after learning python skills is python developer. A Python developer is responsible for coding, designing, deploying, and debugging development projects, usually on the server (or back-end) side. However, they can also help organizations with their technology framework.

Responsibilities

  • Build websites
  • Troubleshoot data analysis issues
  • Write codes that are both reusable and efficient
  • Optimize data algorithms
  • Implement data protection and security

Data analyst

One of the most common uses of Python is its ability to quickly create and manage data structures. Pandas, for example, offers a plethora of tools for manipulating, analyzing, and even representing complex data structures and datasets. Additionally, you can use Python / R to write your own data analysis algorithms which can be directly integrated into your business intelligence tools through the API.

Responsibilities

  • Results analysis
  • Report results to relevant members of the company
  • Identify patterns and trends in datasets
  • Work alongside teams within the company or the management team to establish the needs of the business
  • Define new data collection and analysis processes

Software developer

The role of a software developer is to identify, design, install and test a software system that they have designed entirely for a business. This can range from creating internal programs that can help businesses be more efficient, to producing systems that can be sold. When software developers deliver a software system, they also maintain and update the program to ensure that any security issues are resolved and that it works with new databases. Python is a common language used in the software development process, making knowledge of the language the key to landing a job as a software developer.

Responsibilities

  • Software research, design, implementation and management
  • Test and evaluate new programs
  • Identify areas to modify in existing programs and subsequently develop these modifications
  • Effective code writing and implementation
  • Determine operational practicality
  • Development of quality assurance procedures
  • Deploy software tools, processes and metrics.

Python Web Developer

A Python web developer is responsible for writing server-side web application logic. Python web developers typically develop back-end components, connect the app to other third-party web services, and support front-end developers by integrating their work with the Python app.

Responsibilities

  • Reusable, testable and efficient code writing
  • Integration of user-oriented elements developed by front-end developers with server-side logic
  • Design and implementation of a low latency, high availability and performance application
  • Write reusable and efficient code.
  • A Python expert, with knowledge of at least one Python web framework such as Django, Flask, etc.
  • Basic understanding of front-end technologies such as JavaScript, HTML5 and CSS3.

Full-Stack Developer

A full-stack developer is someone who works with the back-end of an application as well as the front-end. Full-stack developers need to have skills in a wide variety of coding niches, from databases to graphic design and UI / UX management to do their jobs well. The full engineer job description typically includes the use of a range of different technologies and languages ​​to develop applications. Full Stack developers approach software holistically, as it responds to both user experience and functionality.

Responsibilities

  • Software design and development assistance
  • Test and debug the software to keep it optimized
  • Writing clean code for the front and back end of the software
  • Design user interactions on the web application itself
  • Creation of servers and databases for the software back-end
  • Ensure cross-platform compatibility and optimization
  • Test and maintain responsive application design
  • Work with graphic designers to design new features
  • Development of APIs and RESTful services
  • Keep abreast of technological advances to optimize their software.

Product manager

Product managers always assess user data and audience behavior to help guide product decisions. Python can be useful for effectively evaluating data in order to make smart business decisions.

Responsibilities

  • Define the product vision, strategy and roadmap.
  • Collect, manage and prioritize market / customer needs.
  • Act as a customer advocate by articulating the needs of the user and / or the buyer.
  • Work closely with Engineering, Sales, Marketing and Support to ensure business and customer satisfaction goals are met.
  • Has technical product knowledge or expertise in a specific area.
  • Running beta and pilot programs during the qualification phase with near-finished products and samples. In Agile environments, regularly reviews completed work and checks with customers to ensure it meets customer expectations.

Machine learning engineer

Over the past two years, vacancies for this position have increased to around 330%. If you are proficient in Python, you will be given preference over other candidates. The role of a machine learning engineer is to build and train machines, programs, and other computer systems to apply them to making predictions. Python becomes ideal for this role due to its ability to automate data and its algorithms.

Responsibilities

  • To study and convert data science prototypes.
  • Design and develop machine learning systems and schemes.
  • To perform statistical analyzes and refine models using test results.
  • To find datasets available online for training purposes.
  • Train and retrain ML systems and models as necessary.
  • To extend and enrich existing ML frameworks and libraries.
  • Develop machine learning applications based on client / client requirements.
  • Research, experiment and implement appropriate ML algorithms and tools.
  • Analyze problem solving abilities and use cases of ML algorithms and rank them according to their probability of success.

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