Companies of all sizes have started to realize the importance of acquiring skilled workers that can analyze a large amount of data and inform them about the best course of action for their business. So, it’s not a secret that data scientists have been one of the most in-demand jobs in the digital era.
However, becoming a data scientist comes with a set of skills for data science that might help you excel in this sector.
Learn in This Article
- Skills for Data Science
- Technical Skills
- Probability and Statistics
- Knowledge of Machine Learning
- Cloud Computing
- Non-technical Skills
- Strong Communication Skills
- Problem-Solving Skills
- Data Intuition
- Technical Skills
Skills for Data Science
If you’re interested in data, pursuing a career in data science could be your best shot. As of today, data scientists are among the hottest careers out there.
As already mentioned, companies are constantly on the lookout for individuals that rely on data to help them improve customer retention, find new and innovative opportunities, and stay on top of the competition.
Below we’ll take a closer look a the top skills required for a data scientist—separated into technical and non-technical skills.
Some data scientists hold a Ph.D. or a Master’s Degree in statistics, computer science, mathematics, or engineering. It’s clear how the educational background can provide a solid foundation for data scientists.
Besides data mining, visualization, and statistical skills for data science, you should be aware of a set of other technical skills.
First and foremost, knowing how to program is an essential step to becoming a data scientist. While many companies can be picky about which programming language to use, Python, R, Perl, SQL, C++, and Java are among the most preferred ones. These programming languages aid data scientists in the organization of unstructured data.
Unfortunately, this career path can be a challenging endeavor if coding and programming skills for data science are lacking.
Probability and Statistics
Especially if the company’s stakeholders rely on data for decision-making, probability and statistics are both vital skills.
As data science uses algorithms and capital processes to gain more insight into the company and make solid decisions. Not to mention, these data scientists’ technical skills help the professionals make accurate predictions.
Knowledge of Machine Learning
Machine learning is an essential skill, especially if you’re working for a firm that handles a massive amount of data where decision-making is everything. Similar to probability and statistics, machine learning contributes to data modeling and its outcomes.
Some machine learning software include PyTorch, TensorFlow, Random Forests, Naive Bayes, and Keras.
It’s true that data science and cloud computing often go hand in hand. In fact, data science frequently incorporates the use of cloud computing products and services to assist data professionals in gaining access to the resources required to manage and process data.
Because cloud computing allows data scientists to access databases, frameworks, and programming languages, tools like Azure and Google Cloud can make quite a difference, especially when it comes to storing all the company’s information.
Although these data scientist skills might come off as intimidating, it’s possible to take part in Massive Open Online Courses (MOOCs) or bootcamps that will give you a more hands-on approach to the job of a data scientist.
Having an excellent technical skillset is not enough to be a top-notch data scientist—non-technical capabilities can make a difference too. Let’s explore some of the most important ones.
Strong Communication Skills
Data scientists are well aware of how to extract, comprehend, and analyze data. However, many don’t place the same importance on communicating these findings to their team.
In fact, your team members don’t have the same knowledge and background as you do. In this case, it’s important to communicate the results of your research in a way that’s easy to understand.
Handling and solving problems will be one of the most critical roles of working as a data scientist. Technical knowledge and an innovative mind can both bring out the most effective solutions.
When feeling troubled, it’s recommended to break down the issue at hand into various sections and align them in an organized manner.
In addition to getting talents with both experience and training, companies want someone with an intuitive mind on their team.
In fact, understanding a massive set of data isn’t always obvious. That’s why competent data scientists use intuition to analyze information beneath the surface.
Skills for Data Science: Key Takeaways
- Data scientists need both technical and non-technical skills.
- Apart from data mining, data scientists must know how to program and have knowledge of machine learning, cloud computing, and statistics.
- Problem-solving, communication, and intuition are among the most important non-technical skills every data scientist should have.