Data science is a very lucrative career option, especially considering how much of the world revolves around data in our daily lives and how different organisations can leverage this data for their own benefit. There are so many data career options to explore, and this is why a lot of people get confused once they start looking into a career in data science. If you are wondering if this is the right career for you or whether you are the right fit for data science, here is everything you need to know about getting into data science.
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What is Data Science?
Data science primarily involves preparing data for analysis. During this preparation, a data scientist cleans the data, aggregates it, and manipulates it so that it can be used in data analytics. In some cases, data scientists can be tasked with collecting the data that they then prepare for analysis. Data scientists work closely with data analysts to uncover patterns and to use these patterns to help business leaders make informed decisions based on the insights gleaned from the data that has been collected and analysed.
Data scientists are curious about data, what it says, how to manipulate it, and how to use it meaningfully. In addition to their passion for making an impact on businesses and organisations, data scientists have exceptional judgment to help them know what data to collect as well as what data would be useful in different situations, as well as an analytical mindset with strong problem-solving skills. Because data science is always changing, the best data scientists have a strong willingness to learn about new technologies, methodologies, skills, and tools.
What Does a Data Scientist Do?
In the modern age, most data scientists use machine learning models to solve nagging business problems. They also utilise statistical natural language processing to mine data and to extract insights from this data. Although data scientists mainly work with unstructured data that they prepare for analysis, they also deal with structured data. Data scientists use complex algorithms and statistical methods to analyse structured data. They then visualise the data or work with data analysts to use the data to tell a story and to provide insights.
Data Scientist Career Path
While it is possible to become a data scientist soon after graduating from college, many data scientists start on a data architect or analysis path. This is so that they can have a better understanding of how data is used, and so they can know what those they will be working with once they become data scientists expect of them. It is also possible to branch out into other areas once you become a data scientist, but that depends on what you want your career to look like. To become a data scientist, here is what you need to do.
Get the Right Education
Indeed, you do not need a master’s degree to become a data scientist. However, a bachelor’s degree is unlikely to get you to the highest echelons of a data science career. Once you graduate with a computer science degree, you can work in the data science field to gain the necessary experience and to decide whether this is the right career for you.
Once you have a few years of experience, you can then enroll in a computer science masters degree program at Wilfrid Laurier University or a similar school. Once you have the master’s degree, you can apply for senior data scientist roles, as you will have the skills to get into these positions and a clear demonstration that this is the path you would like to follow.
Non-traditional Path
Although it is expected that a data scientist completes the requisite university education, things are changing now. Many companies want a demonstration of skills and competencies instead of university degrees and transcripts. Because of this, many companies are now open to hiring data scientists who are self-taught. In many cases, you need to have completed a Bachelor’s degree in Computer science but all other advanced training such as Python, NLP, SQL, and others can be completed online. Additionally, many universities do not teach new tools like TensorFlow so you might have to complete an online course for some of these latest data science tools.
Give Yourself an Advantage
The demand for data scientists is very high right now. However, getting a job as a data scientist in the fields you like might be challenging, as the criteria for selection are usually very strict. To give yourself an additional advantage, you’ll need to have some background in social sciences, economics, natural sciences, mathematics and statistics, engineering, and machine learning. Ideally, you should also have some programming experience in languages such as Python, R, SQL, and others that are extensively used in data science.
Skills and Qualifications
To stand out as a data scientist, you need to have several skills and qualifications. In addition to Python, R and SQL, here are other technical skills you need:
- An advanced understanding of machine learning, data science, and data models
- Learning and analytical skills
- Experience with natural language processing techniques and algorithms
- Experience with deep learning tools such as TensorFlow
You also need other generic skills such as a drive for performance, a desire to come up with unique solutions to problems, and soft skills like strong communication skills and the like. If you are looking for a Data Science job, visit Jooble.
How Much Do Data Scientists Earn?
A lot of people get into data science because they are fascinated by data and love the continuous learning process that the career entails. Having a good salary accompanying your passion is great, and data scientists earn an average of $100,000 in their first year according to information on PayScale and Glassdoor. Senior data scientists can earn anywhere from $150,000 annually, excluding bonuses that are added to their base salary.
A career in data science is challenging, but also interesting due to the ability to keep advancing and learning while you work. There are at least two ways to get into data science, but remember that you might need an advanced master’s degree if you would like to rise to the level of a senior data scientist.