SHOULD I PURSUE A CAREER FOCUSING ON ANALYSIS OR DEVELOPMENT?

Making big decisions and investments is never easy, especially when it comes to choosing a career direction.

At Lantern we commonly come across prospective students and professionals who are unsure of their choice. They are interested in employment in tech but don’t know which position or field they should pursue. This is quite an understandable dilemma. Especially given the rise in popularity of data science careers in recent years and the wide range of jobs included in the field.

For this post, we’ll take a look at some key aspects to consider when choosing your next career. We’ll focus on Data Science vs. Software Development since Lantern specializes in the analysis and development fields. However, the concepts outlined in this article can easily be applied to all sorts of career employment choices.

TOPICS COVERED

  • WHAT DO YOU BRING TO THE TABLE?
  • HOW MUCH DO YOUR VALUES COMPARE TO COMPANY VALUES?
  • WHAT YOU LIKE VS DON’T LIKE
  • EDUCATION? TRAINING?

PERFORM A SELF ASSESSMENT

Just like with any important decision, you should start with some self-reflection. Choosing a career is no different. You should consider several factors. What type of work environment do you want to work in? Do you enjoy certain tasks more than others? What type of people do you want to work with? Etc.

Let’s break down some things to include in your self-assessment.

WHAT EDUCATION AND SKILLS DO YOU CURRENTLY POSSESS?

Similar to when you want to map out your career path, you need to get an idea of where you stand. Start by assessing your current level of education, technical skills, and soft skills. This will help you get a sense of what is within reach and what requires more training to pursue.

When it comes to data science vs. software development there is a lot of overlap in this case. Both require some form of university-level education. Some data science positions also prefer applicants with Masters and Ph.D. degrees, though it’s not always required. Depending on the job level in either field, the soft skills are similar as well.

WHAT VALUES ARE YOU LOOKING FOR IN A JOB?

Next, take some time to identify the requirements you have for a job. These can range from things like salary and location to benefits, to job-type and travel.

Even if you’re already set on a tech job in analytics or development you should do this step. It won’t necessarily help to decide between the two but it will help you when it comes time to search for positions.

WHAT TYPE OF TASKS DO YOU ENJOY?

When considering between fields, this is crucial. Evaluating the type of interests you have will help you see which is a better natural fit for you. This should include the types of habits and hobbies you have.

For example in the analytics field, the focus is on working with data and extracting meaningful information from it. In contrast, the development field is focused on building a product for consumers to utilize. Maybe you’re the kind of person who likes to work with numbers and graphs. Or you find yourself looking at trends and patterns to try to predict future events. In this case, you would likely enjoy working as a data scientist.

On the other hand, perhaps you like building. Starting from an idea and working towards a final product that showcases the hard work that went into it. Then you w better suited for software development.

HOW DO THE FIELDS COMPARE?

After the self-assessment, you should compile a list of careers you would be interested in learning more about. At this stage, we want to work out the full requirements of those jobs and the type of work it entails. This way you can compare them to your self-assessment and find the best-suited position.

WHAT ARE THE EDUCATIONAL REQUIREMENTS?

Just as the self-assessment includes an evaluation of your current education, you should now consider the job’s educational requirements. This will help you see what you are missing and how to reach the required level.

For data science and software development, educational requirements can actually be quite flexible. There will be preference given to candidates with relevant education as well as experience. But, large tech firms, typically hiring for these positions, place a bigger emphasis on proven knowledge and experience. That’s why the hiring process includes technical interviews. And also why getting hands-on training with relevant and applicable work is so important.

WHAT TYPE OF TASKS ARE PART OF THE JOB?

To complement the consideration of the tasks you enjoy, you now need to consider the tasks that are required of the job. You can make a list of both and see how much overlap there is for a given position or career.

Again, this part is crucial. Ultimately if you don’t enjoy the work you will struggle to get very far. If your interest in a job stops at the salary you will not have the motivation required to pursue the education and training necessary. It’s best to figure this out before investing time and money in a career that won’t provide you with job satisfaction.

As far as analytics and development are concerned there are many similarities and many contrasts. Both fields are tech-oriented leading to computer-centered office jobs. Typically you’ll work as part of a team but have your own responsibilities for sections of a project. They both require technical knowledge of various software, practices, and programming languages. The specifics of which software and languages will vary greatly better the fields and jobs within each field.

Let’s break down the differences now. Modern software development follows an agile workflow process. This means that a plan for the software is defined at the start of the project. The development goes through iterative stages where the plan is modified. This results in a project that maintains clear development goals but is flexible to changing product requirements. Furthermore, as a developer you are interested in the proper implementation and innovative design of the software. You can find a more complete list of responsibilities on GlassDoor.

In data science, projects can follow a similar agile structure. But with more ambiguity for how tasks are meant to be completed. Data scientists focus less on good code design and more on the analysis of data. They need to be fluent in statistics and mathematics to be able to accurately develop data-driven solutions for businesses. Positions do involve programming, but more so as a means to an end rather than the focal point. For a list of responsibilities check out its GlassDoor page.

WHAT TYPE OF TRAINING WILL I REQUIRE?

Once you have narrowed your decision you need to factor one last aspect. Namely, if you will be able to achieve a career in the field. If you require extensive training then you need to factor in if and how you will receive said training. This should include your time availability, the cost of training, how long your training will take. Luckily with ready internet access, more and more training programs are available online.

For those interested in either data science or software development this is also the case. Lantern Institute has programs taught and mentored by experienced industry professionals to help you get the essential hands-on training necessary. Check out the programs page for more details.

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