Is Python Enough to Get a Job?

Over the last several years, Python has evolved into one of the most sought-after programming languages in a varity of domains that include Website Development, Data Science, and Machine Learning. If you currently work in these domains, I am sure you realize how a high competency level in Python can provide a boost to your career. However, if you are just getting started with your professional journey in such domains, it is natural to wonder if knowing Python alone is sufficient to get you a job? 

Knowing how to code with Python is enough to get hired in entry-level jobs, but your chances of getting hired are increased if you have skills related to the company’s industry. Companies hire problem solvers who use Python, so build projects using Python and put them in your Github.

Your background, interests, and career goals affect how much Python you need to land a job. This post will serve as a guide to finding a job as a Python programmer. 

Important Sidenote: We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and identified 6 proven steps to follow for becoming a data scientist. Read my article: ‘6 Proven Steps To Becoming a Data Scientist [Complete Guide] for in-depth findings and recommendations! – This is perhaps the most comprehensive article on the subject you will find on the internet!

How Much Python Is Enough to Get a Job?

The amount of Python you will need to get a job is based on what type of job you want. Companies hire Python programmers to help them solve a problem, whether it be to sell more products, work more efficiently, process and sort data, or develop websites and applications.

The Basics

To get started, you need to learn the basics. These include:

• Understanding the syntax and Python shell, control structures, strings, looping, and exception handling are essential
• Object-oriented concepts to structure your code
• Lists and their functions and string formatting
• Parallel programming—mutual exclusions, locks, deadlocks, and race conditions

Networking Concepts

These basics will get you to the point where you can write parallel programs in Python. The next step is to learn how to write code that communicates through a network. You will learn to use sockets to write echo programs, use request modules as you play around with HTTP, and start using debugging tools.

You are now ready to write code to solve problems.  

Analyze Your Code

However, if you do not know how to analyze your code, you cannot fix problems in it. For that, you need to become familiar with data structures and algorithms. This will include dynamic programming, linked lists, hash tables, trees, stacks, graphs, and queues.  

What Kind of Jobs Can I Get Knowing the Basics of Python?

Once you can write code in Python and analyze it to fix bugs and problems, you are ready to begin working. But do not count on landing a job at one of the big firms that pay the high salaries you read about.

Instead, look for internship opportunities or jobs at small companies or start-ups. Use Indeed, LinkedIn, and similar sites to find them. These small gigs are stepping-stones that can give you experience and help you pay the bills.

You will need other skills at this stage, including networking, job search, and people skills, to find a job and get hired.

Does Knowing Other Languages Help Me Get a Job? 

Knowing other languages, like Java or R, benefits you in two ways. First, it makes learning Python easier. What might take months if you have no programming experience can be done in weeks.

Along with this, another consideration is how much time you will devote to learning the language. It’s essential to look at a program’s time expectations. A site that says you can learn Python in 30 days might be assuming you will spend 40-50 hours a week to make that happen. If you do not have that much time, it will take you longer.

The second benefit to knowing another language is it increases your chances of getting hired. Most companies hire someone with a set of skills. Look at job sites. You will see that most postings mention SQL, JavaScript, and other skills needed for that industry.

Preparing Yourself to Specialize

Let’s say that you have learned enough Python to land an entry-level job and are ready to move up. It’s time to target a technology or industry. Let’s go over a few.

Web Development 

Do you know the difference between extending Python in a web server and using a Web framework to write server software using Python? Can you create web-scalable software and use JavaScript? Those are skills you need to learn for that industry.

As more servers are stored in the cloud, you should also familiarize yourself with tools such as Amazon AWS and OpenStack’s official clients.

Data Science

Many programmers working in data science prefer Python (although R is another popular program). Data science also requires a strong foundation in SQL (Structured Query Language). You also need to be familiar with the following Python libraries—NumPy, SciPy, and Matplotlib. 

• NumPy will efficiently process tons of data and is used for multi-dimensional array operations.
• SciPy is for numerical integrations, gradients, derivatives, and other operations. It is a Python library commonly used to solve mathematical problems.
• Another library you need to become familiar with is Matplotlib, which creates graphs and charts.

Machine Learning

When programs like Netflix can make recommendations tailored to you or Alexa can understand what you said (at least most of the time), they are products of machine learning.

The idea that computers can be programmed to learn on their own is at the heart of machine learning. Demand for programmers skilled in this area is high. And Python is the go-to language in this field.  

Python libraries you need to become familiar with for machine learning applications include sci-kit-learn, TensorFlow, and PyTorch. These libraries help you understand how machine learning algorithms work.  

You should also have a strong foundation in math and statistics to be successful in this field.

Do I Have to Have a College Degree to Get a Job Using Python?

To land the more advanced, higher-paying jobs, a college degree in computer science or a related field is often required. Data scientists often focus on statistics or math and take some computer science courses.

However, experience counts for a lot as well. As your career advances, your reputation as a programmer and the products you have created might be enough to overcome the lack of a degree.

Also, investigate certifications for Python and other programs to advance your career.  

You Have to Be Prepared for the Coding Interview to Land a Job 

Although being prepared for questions you will find when you google interview questions is not a bad idea, do not spend too much time prepping for them. A job interview for coding is an interview about your technical ability.  

Be prepared to show your expertise in these areas for the interview:

• Data Structures and Algorithms. Be familiar with terms such as binary search, dynamic programming, linked lists, trees, and graphs. Understand data structures and algorithms and be able to explain how to use them to write efficient code. These are the most frequent and most important questions.
• CS Fundamentals. Although slightly less frequent, questions about computer systems are just as important. Expect questions about networks, system design, and operating and distributed systems. Interviewers like to ask these questions because most candidates focus on the commonly asked data questions. Be prepared to answer questions about caching, virtual memories, or DNS.
• Resume and Non-Technical Questions. Resume questions play less of a role in an interview than many individuals think. The key is, to be honest when talking about your resume. As to questions about your personality, they are not nearly as important as your technical chops. Interviewers want to know if they will be able to communicate and work with you. Your goal is to have the interviewer enjoy talking with you.

Make Sure You Know Your Monty Python

As you learn Python, you will sometimes see references to Monty Python. Those are not accidents. The creator of Python, Guido van Rossum, is a fan and watched Monty Python movies while developing the language. References such as spam and eggs and articles that mention the Holy Grail of Programming are examples.

Do you have to like Monty Python? No, says the Python website’s FAQ page, but it doesn’t hurt.

Conclusion

Python is enough to get an entry-level job. But to advance in the data science field, you will need to master additional skills, such as having a solid foundation in SQL or a familiarity with other languages. Remember that a company does not want a Python programmer but someone who can use Python to solve problems.

BEFORE YOU GO: Don’t forget to check out my latest article – 6 Proven Steps To Becoming a Data Scientist [Complete Guide]. We interviewed numerous data science professionals (data scientists, hiring managers, recruiters – you name it) and created this comprehensive guide to help you land that perfect data science job.

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