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Is Data Science a Good Career | Ethan's Tech

Is Data Science A Good Career

Is Data Science a Good Career | Ethan's Tech
The world is advancing every second and the world of science is taking thousands of turns every year. Data science is the most demanded part of technology in this 21st century. Teenagers, young adults, adults everyone is now attracted to the world of computers rather attracted to the world of the internet.  As time advances the craze and curiosity to get into the world of the internet also increases. Now the internet plays a big role in our lives and this internet has various parts which integrate all sorts of data. 


Data science is a perfect amalgamation of maths, programming, statistics, and artificial intelligence. It is one of the most required aspects of science which is helpful in everyday life.  Data Science helps in transforming raw data into insights. Data science provides a meaningful meaning to everyday numbers. Data science is placed in one of the growing communities.  Most of the data science tasks are related to the data that are collected from the footprint of the people left on the internet. In today’s time, we all are leaving our footprints on the internet.  Every time people interact through phones, the internet, or computer they generate data. And most of the time the data gets collected and stored and then handed over to the data scientist to generate the insights and help the companies to make a profit out of the data.  Data science involves the collection of data, analysis of data, and building models from that data. Machine learning also comes under data science. The only difference between a machine learning engineer and a data scientist is that the machine learning engineer focuses on the machine learning algorithm and a data scientist focuses on the overall pipeline of the data. 


As the world of the internet is evolving and getting better with each passing day The opportunity for data science as a career is getting wider for people. Data science is going to provide plenty of opportunities in space.  According to a survey the average data scientist in the US makes around $120000 per year. But this number can have tremendous variation. Within the US the data scientist could be making more than $120000 per year at specific tech companies. 


Data Science has a fairly unique spot. It’s an exciting career with tons of job opportunities. One needs to possess a few basic skills before getting into the field of data science so that he/she can sustain in the field of data science for a longer duration. Below are a few skills mentioned.  Marketable skills like Data visualisation and programming –  One can’t become a data scientist without strong programming skills. Studies have found that people who are proficient in python and SQL are likely to remain in the field for a longer duration.  Knowledge of mathematics and statistics– Mathematics and statistics can be called a building block of a data scientist career. Even the understanding of data needs good command over statistical knowledge.  Machine learning –  Machine learning is an essential skill to have for building a career in data science. There are various types of machine learning and applying the appropriate learning type can give quality predictions and estimations.  Communication skills for sharing the work with stakeholders –  If a person wants to build a career in data science then needs to have good communication skills to be able to interact with other teammates and stakeholders. Communication skill is something which is much needed now in every type of field. Attitude to learn more and accept the change –  The world of data science gets updated every single day so the person trying to create a career out of data science should have the attitude to learn more and should be able to be a part of the change and accept the change positively.


Now the majority of teenagers and young adults are getting into the world of data science. They find data science to be a really fun subject to read and make a career out of it. Everyone is now learning programming, and coding and most of them take their interest in data science further and make it their profession.  So everyone interested in data science and has the curiosity to learn more and implement those learnings in generating new data should get into the field of data science. This is a kind of career option which gets updated every single day so people who live in have to cope with the new changes happening. 


20 to 30 years before there was no such term called data science. The existence of the internet was just beginning and the collection of data had just started. At that time Excel sheet was the most chosen option to store various types of data.  Data in the previous years was not much wider space as it is now. Previously the amount of data was so low that one could easily calculate and extract the insights by just looking at it. And not much effort was needed to transfer the huge data to insights.  Because at that time huge data consisted of 300 to 400 rows of data. But today the scenario is quite different. Now we have millions and billions of rows of data. Now If a person spends his entire life taking out insights from the raw data then he would be unsuccessful because now the data is vast. During the 90s only a few rich people who had seen technology from a wider view knew about the existence of the internet and only a smaller amount of data could be generated.  And after that various types of applications started getting built and creating the present we are right now. These applications influenced people to go online and sometimes people got addicted to these apps. A large amount of data got collected and that’s when the need for a person who could extract insights from the data through computers so that through those meaningful insights some excellent decisions could be made.  As time evolved machines, computers, and the amount of RAM, and storage in the computer, our approach towards technology is getting improved a lot and even the machines are becoming a lot more powerful. 


Data science jobs are being increasingly searched in the last 5 years. And it has been found in a study that data science is going to create around 11 million job openings in the world by 2026.  Data Scientist – A data scientist is a person who changes the data into meaningful insights that a layman can even understand. The role of a data scientist varies from company to company. Business Intelligence analyst – Business analysts join both IT and business in the most profitable way. They possess a blend of business vision, consultant abilities, and understanding of data.  Data Engineer – They are professionals who could transport and transform data in such a way that by the time data reaches an end user like a data scientist they are in a highly usable format. Data engineers are a kind of software engineers that focus completely on data building.  Marketing analyst – A marketing analyst needs to gather data using a variety of methods. They even need to analyze statistical data to better understand consumer behavior.  Data architect – The data architect creates the database from scratch. They design the way the data will be retrieved, processed, and consumed. They take care of improving the data collected and stored.  Machine learning engineers – They take care of the models that are running behind a particular data set to check if they are always performant and are responding within the SLA expected from them. They scale the algorithms. 


Data science isn’t all sunshine and rainbows. Sometimes it gets stressful for the people working on it. And there may be various reasons for data science becoming stressful. People may find it difficult to cope with deadlines and workload. Most people are looking out for an engaging career and a good work-life balance. And when the work isn’t engaging people to lose their desire for it and if it takes people away from their families then also people seem uninterested in the work.  The job of data analyst and data scientist focuses more on human interaction. New Technologies, new methods, and new systems are put into place every single day so people get to learn a lot in this field. Data scientists need to keep up with the changes that are happening within their respective organizations. If the employee doesn’t have an appetite to continuously grow his/her knowledge and skills then he/she might not have a long career in this profession. There’s no need to learn every new tool or read every research paper that comes out. A person just needs to be comfortable with picking up new skills and he or she has to have a system and habits in place to be able to pick up a little bit more every day.  The jobs of data science have a pretty steady schedule where people don’t have to work tremendous amounts of overtime. Depending upon the company one can expect to work fairly consistent weeks of maybe 40-50 hours. People in tech companies have far better earnings per hour than in some other domains. Data science is one of the most flexible careers in the technology domain. 


Data science is on the list of most demandable careers And it has been said by Harvard business review in 2012 that data science is one of the sexiest jobs of the 21st century. But just because a career is sexy doesn’t mean that it is enjoyable or doesn’t mean that it is a good career.  The searches for data science jobs are up but that doesn’t mean the market’s getting more saturated and people are interested in landing a role. Most people don’t realize that data science at most organizations is fairly rudimentary. Many companies are currently building their infrastructures out and they’ll continue to hire data scientists as these organizations mature.  There’s been a massive boom in hiring data engineers. Some studies show that data science will continue to remain important and in demand after many of these companies reach their next stage of data maturity.  Apart from the saturation part people are worried about automl and the work will be automated away in the foreseeable future. Even though this won’t be the case any time soon. The nature of data science roles might change slightly but will always need people to analyze the data, run the models, explain the finance to stakeholders and look at accountants.  Many data science jobs are poorly defined. Even at the entry level, it depends on the person on how he/she can create value for the team. In most organizations, people are expected to do individual work like building models and cleaning data and they have to communicate finance to the stakeholders. Here the employee has the opportunity to work directly with stakeholders to make sure they are getting good value from the analysis. 


Every career path has some good and some bad points so how can data science get skipped? After every good and bad point, it’s the interest of the person that matters the most to make him/her stick to the profession of data science.  If you think you are capable enough and data science is the only thing that has your whole heart then data science can be proven to be the best career path. And there’s nothing called a good career or a bad career. If something interests you and you’re good at something then that profession is worth following. So data science is today’s new trend but that doesn’t mean your dream is not worth the effort. 
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