Data science is a fast-evolving field offering unlimited opportunities for savvy and career-minded students. If you find that you’re drawn to this exciting area of study, and you’re ready to challenge yourself—data science could be an ideal career path for you.

Before you decide whether to pursue a career in data science, you should be aware of what awaits you, and how you can prepare yourself. This article addresses key aspects of any data science job that beginners should understand before committing to the field.

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What Is Data Science?

Data science involves the extraction of nuanced insights from data using statistics, algorithms, scientific methods, math, and other techniques. In simple terms, data science means using data to help with problem-solving and decision-making. Data scientists collect raw data and convert it into meaningful information.

This process involves multiple steps that can be divided into the following subdomains:

Skills Required to Become a Data Scientist

Listed below are the important skills you need to work on to become a data scientist:

  1. Statistics: Having a background in statistics or a degree in the field can be really helpful. You should also develop experience in descriptive statistics, percentiles, probability, random variables, exploratory data analysis, and cumulative distribution function.
  2. Programming: You’ll need to become an expert in at least one of the main programming languages. Knowing R or Python is a prerequisite in many companies for data scientist positions.
  3. Machine Learning: For many companies, machine learning is not a prerequisite but it’s certainly a preferable skill that they’ll look for in a candidate. Knowledge of machine learning—including logistic regression, decision tree, reinforcement learning, and supervised and unsupervised machine learning—will distinguish you from your competitors.
  4. Data Visualization: Visual representation of data is extremely important in data science. You should know how to use various data visualization tools such as Kibana, Datawrapper, Tableau, ggplot, d3.js, and Matplottlib. These tools are used to convert complex data into a format that is interesting and easily understandable.
  5. Apache Spark: This is currently one of the most popular big data technologies as it helps data scientists to run algorithms much faster. It can also help you deal with unstructured data sets. Using Apache Spark, you can easily prevent data loss and carry out your projects smoothly.
  6. Teamwork: Apart from technical and computer skills, you’ll need to work on your communication and teamwork skills, because a data scientist cannot work in isolation. You’ll often work with multidisciplinary teams involving product managers, strategists, marketers, product designers, and other professionals.

Online Tools for Learning Data Science

There are many paid and free tools available on the internet that can help you kickstart your data science career. Below is a snapshot of some of the more popular tools.

How Much Do Data Scientists Get Paid?

Data science is both in-demand and a highly technical field requiring rigorous training and advanced skill sets. Salaries are competitive and depend on your skill level, qualifications, and experience. Even as an intern, you can earn around $33,000 a year, according to Glassdoor. Mid-level data scientists earn an average salary of around $133,000 a year, while a senior data scientist earns somewhere between $134,000 a year and $154,000 a year.

For comparison, below are a few national average salary levels for related job titles:

How to Become a Data Scientist

The following are the steps that can help you kickstart your career in data science:

  1. Read up about the field

It helps to be aware of what you’re getting into. Reading books, blog posts, online articles, and journals about data science will help you understand the field and the opportunities available to you. It’ll help you figure out if data science is the right career for you.

2. Choose an academic path

If you’re sure you want to become a data scientist, then you’ll need to select the right academic path. There’s no specific degree that you need, so you’ll need to decide whether you want to study a bachelor’s degree in statistics, mathematics, computer science, IT, or another relevant stream. A master’s degree in a related field will be even more helpful. If you don’t opt for a degree, you can always choose an open online course or bootcamp that can train you to be a data scientist.

3. Choose an area of specialization

There’s no use studying each and every aspect of data science. It’s best to choose a specialization that encompasses your key interest areas. For instance, you may choose to focus your expertise on business solutions or data visualization. You can then select a specialized course to train you in that area.

4. Get certified

Certifications in the right skills, tools and areas of expertise increase your chances of getting hired because they provide an easy reference point for employers that you have the right knowledge. For example, you can become an SAS Certified Predictive Modeler using SAS Enterprise Miner 7. There’s also a wealth of online certifications available at your fingertips.

5. Find a job

Landing a great job isn’t always easy, but if you have the right skills, qualifications and experience, your chances are much higher. There are plenty of forums, job boards, and recruitment networks, such as Kaggle and iCrunchData, that can help you to find and land a job that’s right for you.

If you follow each of these steps, you’ll be on your way to a successful career in data science. Want to find out more before you invest in a new, data-focused education? Check out our four must-read tips for launching a career in data science. Or get a glimpse of what’s ahead: find out what a day in the life of data scientist looks like.

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