Are you starting a career in data science?

Just thinking about the first step can leave you dazed and confused, especially if you lack previous experience in the field.

With so many different data science careers to explore, you might find yourself wondering which is the right one for you and if you’ve got what it takes to fit the profile.

What is Data Science?

Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. Today, successful data professionals understand that they must advance past the traditional skills of analyzing large amounts of data, data mining, and programming skills. In order to uncover useful intelligence for their organizations, data scientists must master the full spectrum of the data science life cycle and possess a level of flexibility and understanding to maximize returns at each phase of the process.

The Data Science Life Cycle

The image represents the five stages of the data science life cycle: Capture, (data acquisition, data entry, signal reception, data extraction); Maintain (data warehousing, data cleansing, data staging, data processing, data architecture); Process (data mining, clustering/classification, data modeling, data summarization); Analyze (exploratory/confirmatory, predictive analysis, regression, text mining, qualitative analysis); Communicate (data reporting, data visualization, business intelligence, decision making).

What Are The Duties Of Data Scientists And Analysts?

In order to help management make wise business decisions, data scientists and data science analysts are in charge of studying historical user data, forecasting future user behavior, and then delivering these insights to management. Creating statistical and economic models and using cutting-edge machine learning technologies to summarize and visualize data are typical aspects of the profession.

There are two primary ways you can use data science skills to grow data-centric careers: become a data science professional—pursuing jobs like data analyst, database developer, or data scientist—or transition into an analytics-enabled role like a functional business analyst or a data-driven manager. Both career paths require foundational skills and knowledge in data analytics, programming, data management, data mining, and data visualization.

Data Scientists vs. Data Analysts: What’s the Difference?

The skills and job responsibilities of entry-level data science roles and data analysts often overlap. Both roles require statistical knowledge and the ability to program. However, there is a clear difference in the focus.

What Does a Data Scientist Do?

Data scientists answer questions about the business from the context of data. They leverage data to create new product features and tend to do more modeling and open-ended research. They’ll spend a lot of time cleaning data to make sure that it is usable for their models and their machine learning algorithms. When you watch Netflix and see a personalized list of recommended shows, that’s machine learning algorithms and data science at work.

“Predictive data analysis involves more complexity, because it predicts what is likely to happen in the future based on data from the past, or based on doing a data crossover between multiple datasets and sources.”

Why Data Science Remains A Viable Career Option Until 2024 And Beyond?

Let’s look at a few variables that suggest data science will still be a viable career choice in the near future

1. Demanding Career

Today, data is, without a doubt, the most valuable commodity, whether it is perishable or not. Leading businesses, including Google, Amazon, and Meta, use data to improve consumer experiences, increase profitability, and accomplish strategic objectives. The issue is that data is spread out in numerous locations in both structured and unstructured forms. In order to gather data, structure and analyze it, derive useful insights, and present it for informed business decision-making, firms require and will always need data science and people.

Jobs in data science have increased by an astounding 650% since 2012. According to Glassdoor, 1,700 jobs with data science as the major responsibility was advertised in 2016. 4,500 in 2018 and 6,500 in 2020, respectively, were the same. With a 60% increase in job vacancies in the US alone, data science was named by LinkedIn as the most promising job for 2019. Even the Covid-19 crisis had no effect on the need for data scientists, with 42% of these firms experiencing little change and just 8% expanding.

2. Short Supply

From 2012 onward, people began educating themselves for professions in data science primarily through books because there was little material on the internet and no advanced programming languages. Additionally, the conventional school system did not provide degrees in data science or specialized courses for those who desired to pursue a career in the field. The discipline of data science is still relatively new and undeveloped right now. There is reportedly a global shortage of between 1,50,000 and 200,000 dedicated data science workers. Therefore, if there was ever a good moment to pursue a career in data science, it is now.

3. Access to Specialized Programs and Data Science Degrees

Professionals working in data science must have in-depth subject expertise as their job description is always changing. Numerous professional organizations are aware of this and wish to impose certification and licensing criteria on people who work in data science.

4. Future Growth Prospects

Opportunities abound in the field of data science, where demand regularly outpaces supply. According to a survey released by the US Bureau of Labor Statistics, there will be almost 11.5 million additional employment in the field of data science by 2026, an increase of around 28%. Even the World Economic Forum’s Future of Work Report 2020 forecasted that by 2025, data scientists would hold the position with the highest growth and demand.

5. Fat Pay Packages

Even after considering opportunities for advancement, the financial feasibility of a vocation is a crucial consideration in selecting whether to follow it. Additionally, careers in data science do pay well. The median wage in the US is $49,800, according to Glassdoor, while the median wage for data science experts is $1,08,000, which is more than double the national average. Data science specialists with expertise ranging from 3 to 10 years stand to earn anything between 25 and 65 lakhs annually, according to the 2021 India Talent Trends study provided by recruitment agency Michael Page. Experienced people are paid more than one crore.

Technical Skills Required for a Data Scientist

Learning new technologies, approaches and the latest platforms of big data analysis enables data science professionals to stay relevant in the real world, equipping them with practical knowledge and hands-on training.

• Programming Languages: R Programming, SQL (Structured Query Language), Python, Java, C, and C++
• Platforms: Hadoop, Apache Spark
• Data Visualisation: Matplotlib, Tableau
• Machine Learning and AI: understanding neural networks, reinforcement learning, Natural Language Processing (NLP) technologies, recommendation engines

Non-technical skills required for a data scientist

• Analytical skills to analyze data to identify trends and real-world business and industry challenges
• Data scientists’ seldom work in silos, they need to be team players
• Collaborating on multiple projects, data sets, and departments across the organisation is a common feature
• From C-suite to investors and sales teams, data science professionals need to translate incomprehensible data into relevant actionable strategies. So good communication skills and storytelling is a crucial skill.

What is the Future of Data Science in India?

Data Science is one of the fastest-growing fields in India. Data Science job opportunities in India are increasing as organizations seek to harness the power of data to drive decision-making. Some of the most common job roles in data science include data analysts, data scientists, and big data engineers. Data scientist eligibility in India requires knowledge of extracting, cleaning, and analyzing data. Data scientists use mathematical and statistical methods to mine data for insights. 

Scope of Data Science in India

With data being termed as the future oil for organizations, analytics have become an engine that drives it to arrive at meaningful insights. The powerful combination of both is what is driving the future scope of data science. All across the globe, organizations are innovating multiple methods to harness data and use this powerful tool to drive their businesses.

A data scientist has been a lucrative career option for the last few years. Apart from the increasing significance of data and the need to refine it, there are several other factors that have increased the demand for data scientists in India.