07 Jul 2022

Top Seven Data Science Careers That Will Shape Your Future

Ekeeda Moderator
Works at Ekeeda

Top Seven Data Science Careers That Will Shape Your Future 

Data Science has taken the world by its storm and nearly every industry is today highly dependent on data science for potential gains and growth. Data Science is now hailed as the highest-paid job in the world & millions of aspirants are earning lakhs through this amazing field. If you search for future careers in demand, Data science will ace the list.  But did you ever wonder why there is so much uproar about data science in the market? Why do Data Scientists get paid so astonishingly? And why do businesses or processes need data science? Well! Our blog is going to talk about how to get into a data science career and some trending data science career paths that will shape your future.

What Is Data Science?

Data is a vital asset for any business; however, unless you use it efficiently its’ of no use. Data science is something that turns vague data into quite intriguing and meaningful insights that will be used to make crucial business decisions. In simple words, Data Science means to use scientific methods, processes, algorithms, and systems to extract insights from data, and then leverage the data to draw conclusions – in the form of decision making, risk calculation, and targeting the audience to find market gaps and opportunities.  Data processing, data analysis, and data visualizations can be done using R and its corresponding packages. In the market, big sets of data mean big job opportunities since you're in the process of acquiring, data science skills. Data is now the collective currency amongst business owners, tech wizards, and consumers. It pays to know to collect, clean, sort, and analyze data. Whether you pursue a data scientist career or work in any related field, it's worth considering what to expect in the role, what are the key opportunities, and how to make the most of in-demand skills to accelerate your career? And more.

Why Is Data Science Important?

Data Science helps business owners & companies in every form right from your purchasing habits to tracking daily activities, and the importance of gathering data extends much further. For instance, Have you ever wondered how Myntra or Amazon are able to predict your choice or favourite pick of shirt or jeans? Or how does OLA predict your next ride and accordingly equip you with a great travel offer? The most conventional and widespread idea is to build a model to predict the choices that you would pick the next time you come to e-commerce, travel, or any other platform. Applying Machine Learning Techniques to solve these complex problems will give you the required exposure to this domain.

Data Science is not limited to certain industry its spread across every form of industry and process. Today, data science helps to improve public health through wearable trackers to motivate individuals to adopt healthy living habits and can alert people to critical health issues. Data can access your diagnostic report, speed up getting cures for diseases, and even stop the spread of viruses or epidemics. When there is a Covid outbreak worldwide in 2020, scientists were able to track the spread of disease, oxygen and health care equipment, the number of beds in hospitals, and more such things only through the field of data science. This data helped health officials get to lead the outbreak on the war front and prevent it from further getting spread across worldwide. 

Data science is applied critically in every industry or process. For instance, data is used by farmers for efficient crop growth, used by non-profit organizations to boost funding, used by cellular companies for billing, used by payment portals to track payments, used by banks for ledger entries or customer service, and more. Pursuing a career in data science can prove to be a smart move, not just because it’s a trend but because it offers a stable and great career. Data science salary packages are one of the best in the industry. Data very well is the pivotal point on which the entire finance and economy stand out to be.

What Does A Data Scientist Do?

A Data scientist will collect, analyze, clean, and interpret a large amount of data. The data science team will use advanced analytics techniques such as ML, predictive modelling, and algorithms. Basic responsibilities include gathering and analyzing data using various types of data analytics and reporting tools to detect the patterns, trends, and relations in data sets.  

Data Science Eligibility, Curriculum & Skills

        Data Science is a field that has several domains, and it is about the scientific approach to processing huge amounts of data needs. The science of data pertains to various scientific techniques & theories being derived from fields in the context of maths, statistics, computer science, information science, and domain knowledge. 

Eligibility For Data Science

Anyone, whether a newcomer or a working professional who is willing to learn Data Science can opt for this amazing field. Right from Engineers to MBAiates, Software and IT professionals to sales & marketing professionals anyone can opt for part-time or online certified programs in Data Science to upgrade their career. For regular courses in Data Science, basic graduation subjects are the minimum requirements.

If you have studied computer programming, then it would be an additional benefit. Students have to study the fundamentals and advanced in Data Science. Based on your subject command of statistics, Machine Learning, and programming, you can become experts to implement Data Science Techniques in your professional journey.  

Besides, students or individuals from other streams like business studies are also eligible for relevant programs in Data Science. Business professionals having degrees in Business Administration like BBA or MBA are eligible for higher studies in the Data Science domain. Usually, such professionals will work as executives in the IT or MNCs industry, or be responsible for designing CRM reports, MIS Reports, and business-related DQAs (Data Quality Assessment).

Data Science Curriculum 

Most of the courses or programs designed are either PG or certificate level for graduates. Also, various technical institutes and engineering colleges/universities in India have launched degree-level programs in Data Science & Analytics.

Data Science Skills And Subjects

To secure a spot in Data Science Online Training, you might need a Degree – A graduation from any stream. You don’t need a mandatory Coding Background to learndata science.

  • Mathematics is like a spine of Data Science and Data Analysis, where the model is created by processing mathematical algorithms data. In general, maths broadly covers topics in arithmetic, algebra, calculus, differentiation probability, statistics, geometry, and it's allies.
  • Statistics – Various Statistical concepts will help you understand data, analyze and derive conclusions from data.
  • Data Visualization - It’s about accessing, retrieving data, and performing visualization & presentation with R & Tableau.
  • Data Analysis – Explore Excel and databases to derive valuable insights from the data pool and learn from data attributes and properties. 
  • Hypothesis Testing – To formulate & test hypotheses that will be applied in case studies to solve real business issues.
  • Programming Languages – Though coding is not a mandate for admission to the DS program; however, prior knowledge of languages like Java, Python, R, Scale, etc will be added advantage.
  • Database – A good understanding of databases is desirable such as SQL, Numpy, and Pandas.

Skills Required For Data Science Professionals

  • A good grade and understanding of Statistics, Mathematics, Computer Fundamentals, and ML
  • Proficiency in one or more of the programming languages mostly in Python, R, Java, and more. 
  • Good Understanding of Databases
  • Good knowledge of Big Data tools like Hadoop, Spark, And Tableau
  • Experience in Data Wrangling, Data Cleaning, Data Mining, Data Science Visualization Tools, or Reporting Tools.

Now that we come to know what data science is, the data science skills, and the curriculum, let’s dig further to find the most trending Data science career paths:

Data Scientist - Data scientists should be able to use the art of mathematics, statistics, and scientific methods; use multiple tools and techniques for data wrangling and cleaning. As a data scientist, you will conduct predictive data analytics and AI; and explain how these results will be used to provide data-driven solutions to business problems. Data Scientists require more technical skills compared to Data Analysts. For starters, you should take data science-oriented programs like the ones on Ekeeda – Introduction To Python For Data Science And Introduction To Data Science.

Data Analyst -  As a Data Analyst, you will collect, process, and perform statistical data analyses to arrive at valuable insights for the companies and their businesses. You will transform and manipulate large data sets into usable forms, such as reports or presentations. You will help decision-making by going through important patterns and gathering insights from data to effectively communicate to the company heads and stakeholders, for accurate business decisions. Such modules in Ekeeda Data Science Program will help you start a great career as a data analyst in top tech and start-ups across India – Study Introduction To SQL and Complete Data Analysis.

Data Engineer - Data Engineers prepare, process, and manage gathered and stored data for analytical or operational uses. Like the traditional engineers, these data engineers build and maintain ‘pipelines’ that will connect data from various systems, to make information easily accessible to data scientists. They perform batch processing or real-time processing on gathered and stored data. Due to this, data engineers need to understand various programming languages used in data science such as Python, R, and SQL. 

Data Architect - Data Architect mainly designs and creates blueprints for DMS – data management system that data engineers will later build. Compared to traditional architects, Data Architects are quite visionary as they’re responsible to visualize and design an organization’s data management framework. In addition, data architects improve the performance of existing systems and make sure they’re accessible to database administrators and analysts. You can opt for the Ekeeda data science program that gives a complete overview of AWS cloud concepts and database design. 

Business Intelligence (BI) Developer - BI Developers are specialized engineers who use software tools to transform data into valuable insights to help business decisions. They’re responsible to simplify technical information for everyone else in the firm to make it easy to understand. They create and run reports containing data they find using business intelligence tools, and transform the information into layman’s terms. BI Developers design and develop strategies to assist business users to find the information they need to make better decisions. There are quite data-savvy, they use BI tools or develop custom BI analytic applications to help the end user’s on understanding the level of systems.

Statisticians - Statistics is one of the crucial foundations of Data Science, and many statisticians can easily transition into the data science field. Statisticians are usually responsible to collect and handle BIG data. They decide what data they need and how to collect it. They will design experiments, and analyze and interpret the data, to identify trends & relationships - which can be used to inform the company’s decision-making. Additionally, the daily responsibilities of statisticians also include Design data collection processes, communicating findings to stakeholders, and advise on business strategy.

Machine Learning Engineer - Machine Learning engineers are a group of specialized engineers who focus on research, building, and design Artificial Intelligence (AI) and Machine Learning (ML) systems to automate predictive models. Basically, they develop algorithms that use input data and leverage statistical models to predict an output. Ekeeda has the best data science program that throws light on stats for machine learning and you surely find it useful. Additionally, Machine learning engineers research new data approaches and algorithms to be used in adaptive systems including supervised/unsupervised, and Deep Learning Techniques.

Breaking Into the Field

If you wanna step into the field of data science, there are a number of ways you can prepare yourself to take some of the most challenging yet exciting roles. Perhaps most importantly, you will have to impress your senior managers through your expertise and work experience. One such way you can build those skills and experience is by taking up the advanced Ekeeda Data Science Program

This program is designed to develop excellent data science skills that students or working professionals are seeking. The program offers students or working professionals with a golden opportunity to participate in experiential learning experiences. It allows them to build hands-on experience prior to graduating. What’s more? You even get industry-relevant training, 1:1 live classes, 100+ assignments and capstones, and placement assistance in top techs and start-ups such as Datascope, Tiger Analytics, Cloudera, Brainvire, IBM, Yalantis, Peerbits, etc.

Set a clear Data Science Roadmap which defines the milestones in your career journey. Use the roadmap to track your Data Science Journey, see where you stand in preparation and what is your next move! 

Once you have considered factors like your personal background, interests, and career aspirations, you can enroll in this course and take the next step toward achieving your career goals.

On A Concluding Note –

Data Science is a popular field because of how companies these days integrate data science principles into their daily work and operations. It is no surprise that software companies – including tech wizards like Google, Accenture, Uber, IBM – came out on this. The exceptional growth of big data was created due to the internet, which is closely hooked up with software and technology. Data Science really is about processing a lot of information using various tools & technology.

Next on the list who eye data scientists will be financial services companies that have mushroomed the fintech companies. Finance and Technology combined create fintech companies that integrate technology and innovation in their services & offerings to improve their delivery to customers and give a smooth experience. Since it involves handling a vast amount of data such as customer information, and payments, fintech companies tapped the potential of data science tools to help streamline and optimize their processes and focused on improving their services. 

Is it worth pursuing a career in data science? Well with so many exciting job roles of data scientists, the answer will be definitely YES! However, finding out which career path in data science suits you, will totally depend on your individual strengths, likes, and dislikes. The Data science career path in India is simply fascinating and shows no signs of slipping down in the near future in terms of popularity and opportunities. Data Science will continue to shape and influence businesses and companies’ profits and growth.

Become a master of Data Science by taking up this Online Data Science Program now!

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