What do you think when you hear the term ‘data scientist’?
A professional who tackles huge amounts of data and earns lucrative salaries. It was ranked the hottest job of the year a couple of years ago, and still, it is at the third place in the list of top jobs in our country.
At the end of August 2020, there were 93,000 vacant positions for Data Scientists.
It is estimated that by 2025 there would be 137,630 job openings for Data Scientists in India.
What do you think is the reason behind so many vacant positions? The skill gap! There are many professionals who wish to become data scientists, but they lack some skills and lag behind. The huge difference between the talent pool available and the job positions is still widening. The field of data science is growing with an increase in data generated across the globe.
This is why more and more professionals are looking to pursue courses like Python for Data Science so that they can validate their skills to employers and get hired. There are numerous companies looking for Data Scientists to tackle humongous amounts of data.
Let us explore what a data scientist does and what are the skills of an excellent Data Scientist.
Who is a Data Scientist?
A data scientist is a professional who compiles and analyzes large data sets that may be structured or unstructured. As a data scientist, the main task you have to perform is to collect, process, model, cleanse, and then interpret the findings using everything including technology and industry trends to help organizations cut costs, increase productivity, and help in better decision-making.
A data scientist is a perfect blend of skills such as statistics, mathematics, computer science, and contextual understanding to find trends and manage data.
What Skills are Required to Become a Data Scientist?
Data science is an umbrella term that covers data analytics, data mining, machine learning, deep learning, artificial intelligence, and other related fields. Accordingly, you must possess skills to go with these fields.
Some of the must-have skills to become a successful data scientist are mentioned below.
So, the most important skill as a Data Scientist is statistics, which is obvious. Statistics is referred to as the study of collecting, analyzing, interpreting, presenting, and organizing data. As we know that Data Scientist is all about working with data, this is the most crucial skill required.
Concepts like descriptive statistics and probability theory can help you make better decisions from data.
Cut it short, it’s Python or R. You need a strong understanding of any of the programming languages; if you know both of them, it can be amazing. When you look for the most important skill required for data science in Google, it will answer Python at the top.
R and Python are considered the most widely used programming languages by Data Scientists. The main reason is the numerous packages available to help you in Scientific and Numeric computations.
Being versatile, Python is used in almost all the processes involved in Data Science. It can take data in various formats, and allow you to import SQL tables easily into your code.
R is generally preferred when you need to solve statistical problems.
Data Wrangling and Data Exploration
Since the data exists in all formats (image, text. Pdf, audio, video, etc.), you are required to clean and make it structured to make the access easy and analysis simple. This process is referred to as Data Wrangling. The first step in data analysis is EDA or Exploratory Data Analysis. This involves making sense of data and figuring out questions to be asked and the ways of framing them. Also, you have to manipulate available data sources to get the required answers.
This is done by taking a close look at trends, patterns, outliers, reports, etc.
Data Extraction, Transformation, and Loading
When you have multiple data sources such as MongoDB, MySQL, Google Analytics, you need to extract the data from these sources, transform it so that it can be stored in the appropriate format, then load the data in Data Warehouse where you can analyze the data.
So, you need to know the operations of ETL to become a successful data scientist.
Today, Apache Spark is considered the most widely used big data technology across the world. It is specifically designed for data science to help run its complex programs faster. With Apache Spark, it becomes easy for you to handle large amounts of unstructured data. It also helps you prevent data losses. The speed offered by Apache Spark is incredible.
Machine Learning and Artificial Intelligence
Machine Learning is intended to make machines learn repetitive tasks and act like humans. The machines are trained such that they can think, analyze, and take actions accordingly. This includes reinforcement learning, neural networks, etc. You are required to learn supervised machine learning, logistic regression, decision trees, and other algorithms to solve complex issues while handling huge datasets.
According to a survey by Kaggle, there are few data scientists who possess advanced machine learning skills such as time series, recommendation engine, unsupervised machine learning, supervised machine learning, outlier detection, natural language processing, computer vision, survival analysis, etc.
If you possess a maximum of these skills, you can surely gain a competitive edge over others who don’t possess these skills.
Apart from these skills, the additional skills you are required to develop are:
- Sound knowledge of data visualization
- Hadoop platform
- Handling unstructured data
And the soft skills required are:
- Communication skills (both verbal and written)
- Intellectual curiosity
- Business acumen
Data science is rendered one of the hottest jobs of the 21st century. If you wish to upgrade your career and make a career in this domain, the best and most recommended way is to take up an online training course.
Since Python is considered the most required skill for data scientists, you should acquire it well. There are online training courses that help you gain these skills easily according to the level of your knowledge. Along with self-paced learning and round-the-clock learners’ assistance, they also provide career guidance at the end of the course.