In today’s age of technological innovation and digitisation, data is undoubtedly one of the most important resources for an organisation. It is one of the most crucial prerequisites for decision-making. Reports estimate that as much as 328.77 terabytes of data are generated on a daily basis. This has, in turn, led to an exponential growth in the demand for data scientists who can actually analyse the vast amount of data and use it for business purposes.
Some of the many industries that have caused such a high data scientist job demand include retail businesses, banks, healthcare providers, and insurance companies, among others. In order to succeed in this field, you need to have more than just a basic familiarity with code.
This brings us to the question, what are the most important skills required to become a data science expert?
Let’s find out!
What is A Data Scientist?
Before delving into the details of the leading skills for data scientist experts, let’s first understand what is a data scientist and their roles and responsibilities.
Simply put, a data scientist is a professional whose primary goal is to solve complex problems and make crucial data-driven decisions. They are responsible for analysing large and complex data sets in order to identify patterns, understand trends, and find any correlations that can help organisations gain valuable insights.
The responsibilities of a data scientist may vary based on the organisation or the type of business they work for. Nonetheless, listed below are some of the most basic and common responsibilities that every data scientist is expected to fulfil.
- Collaborating with different departments, such as product management, to understand the needs of the organisation and devise plans accordingly,
- Staying up-to-date with the latest technological trends and advancements
- Applying statistical analysis methods and machine learning algorithms to derive insights from data
- Identifying and engineering relevant features from data to enhance both the accuracy and effectiveness of models
- Evaluating the performance of models using various metrics and validation techniques
- Effectively communicating any valuable insights to stakeholders and non-technical audiences.
- Exploring and visualising data via multiple statistical techniques and visualisation tools
Skills Required To Be A Data Scientist
The skills required to be a data science expert can broadly be divided into two types. They are, namely,
- Technical skills and
- Non-technical skills
Mentioned below are a few technical skills that every data science expert must possess
Programming: In order to excel in this field, you must have an in-depth knowledge of the crucial programming languages and not just Python. Such include C/C++, SQL, Java, and Perl. This will help you to organise unstructured data sets in an efficient manner.
Knowledge of Analytical Tools: Having a thorough understanding of the various analytical tools and how each of them operates is also a must for a data science expert. Some of the most commonly used tools include SAS, Spark, Hive and R, among others.
Data Visualization: Data visualisation skills are important for communicating insights effectively. This includes proficiency in various visualisation libraries and tools such as Power BI and Tableau. All these facilitate the creation of interactive and visually appealing visualisations.
Data Mining and Text Mining: A deep understanding of various data mining techniques, such as clustering, or association rules, can also prove to be extremely useful, especially for uncovering hidden patterns and relationships in data. Additionally, you are also required to possess text mining skills such as natural language processing and sentiment analysis to be able to extract valuable insights from unstructured text data.
Non-technical skills also referred to as soft skills, are as crucial as technical skills. Therefore, they should never be ignored. Here are some of the most important non-technical skills you must possess in order to be successful in this field.
Communication: The nature of this field is such that it requires you to communicate with various departments and individuals on a daily basis. Therefore you must possess excellent communication skills so that you can communicate your ideas and thoughts to different team members in an efficient and precise manner.
Strong Business Acumen: Understanding the business context and organisation goals is crucial for every data science expert. You must be able to align all the data science initiatives with business objectives while simultaneously providing actionable insights that will add some sort of value to the overall business.
Analytical Thinking: Other than these, a data science expert must also possess strong analytical thinking abilities. In this manner, you can approach any given problem in a logical and structured manner. You must be able to break down any large and complex issue into smaller and simpler subsets, analyse them individually, and design innovative solutions for the same.
Adaptability: The field of data science is continuously evolving, with innovations and advancements happening every day. Therefore, as a data science expert, you must possess the ability to embrace these new changes and stay up to date with the latest innovations in technologies, methodologies or approaches. In this manner, you will always remain one step ahead of your competitors and eventually gain success.
While all these technical and non-technical skills are crucial for being successful as a data science expert, you are also required to have a strong educational background. This includes a Master’s degree or a PhD in computer science, engineering, statistics, or any other related field. Additionally, you can also opt for specialised courses that are designed to train students who wish to pursue a career in data science.
One such includes the Post Graduate Program in Data Science and Analytics offered by Imarticus Learning. It is specifically designed for fresh graduates and professionals who wish to develop a successful data science career. With the help of this course, you can gain access to real-world applications of data science and explore various opportunities to build analytical models that enhance business outcomes. Additionally, you also get to enjoy several other benefits, such as career mentorship, interview preparation workshops, and one-on-one career counselling sessions, among others.