What is data science?
In today’s times, data science is one of the highest paying career options. With tons of data generated online each day, companies use this data to gain a complete insight into consumer behavior. Data scientists are analytical expert professionals who analyze large amounts of structured and unstructured data to help businesses improve their operations and gain a competitive edge over their rivals. They possess good technical and mathematical skills that help them clean, manage, and organize data operations of a company. Today’s company’s business largely depends on the activities of the users online and this is when a data scientist helps by helping business stakeholders with the information of what people are doing online, what tools they are using, and how these impact their behavior. On the basis of the data provided, business plans are curated to help a company increase its revenue.
What are the skills required to become a data scientist?
Programming skills: In today’s day and age, having good knowledge of programming skills is a must-have for a data scientist. This can help you create your own tool and analyze the data well. Therefore, knowing programming languages such as Python, Java, C++, and others is a must. Additionally, knowing database query languages such as SQL, QL, OQL, and others is required.
Data wrangling: Data is usually messy and being a data scientist you should be able to deal with this and derive valuable insights. You should know how to deal with data imperfections and improper formatting.
Visualization: Picture speaks a thousand words. Similarly, it is important for you to possess good visualization skills to present the data in a visually compelling way. Thus, you will be required to familiarize yourself with several data visualization tools that will help you present the data effectively.
Communication: You should be able to comprehend your technical findings effectively to your colleagues in an effective way as the data will be utilized by them for understanding customer behavior in a better way. Hence, having good written as well as verbal communication skills are necessary.
Teamwork: To get the desired data insights and make the most of customer behavior, you will closely be working with the team of business managers Designers, marketers, and others. Thus, it is imperative that you work as a team.
Problem-solving: Being a data scientist, you will face endless problems, which require you to possess good problem-solving skills.
Curiosity: Being curious will not just help you learn, but also know what sort of questions you should ask when analyzing a new set of data. Being curious will help you gain an insight that surprises you and also increases your understanding of data.
Analysis: You will have to analyze complex data and draw meaningful insights out of the same. The analyzed data can be utilized for experimenting and drawing further insights.
How to be a data scientist?
The career of data science requires you to have good educational qualifications as well as knowledge of various programming languages.
The education criteria include:
Bachelor’s degree in IT, computer science, maths, or any other related field.
Master’s degree in data science or any other related field
Additional knowledge of the below tools and concepts
Good knowledge of mathematics, machine learning, and statistics
Knowledge of Hadoop, Python, R, SQL, Spark and other tools
Should have a keen interest in studying databases and knowledge of how to operate the same
Doing an internship helps greatly
Career path to become a data scientist
The career trajectory of data science includes the following:
Intern: Getting an internship experience helps a lot. As an intern, you will get an insight into the basics of data science. You will learn various programming languages, data modeling, analytic tools, and others.
Senior data scientist: You would be responsible for overseeing the work done by junior data scientists and interns. Your job would involve creating real-time dashboards that display the data of the business. You will also have to spend time on the visualization of the data and conduct an analysis of both structured and structured data sets.
Lead data scientist: Being at a senior level, you would be coordinating with the business stakeholders to understand the data requirements. You would also be assigned work to the team of senior and junior data scientists and would be responsible for delivering the projects as per the given timelines. You would also be developing effective and innovative approaches to solve analytical problems.
AVP-data scientist: You would be leading the data scientist team and would be responsible for the work done by them. You would be identifying the business problem areas and would be delivering analytical solutions for the same. You would also be mentoring other data professionals. You would also be identifying and taking steps to improve the existing data process of the company. You would also be curating plans, strategies to evaluate business plans, and methodologies.
Director-data scientist: You would be spearheading the whole data science team and would be responsible for building and managing the team. You would be the person who would be deciding the tools or software and the data storage systems that should be put to use for storing and analyzing the data. You would take important business decisions and you would also be taking financial decisions pertaining to the company.