How many times have you searched for something online, maybe videos of kittens and puppies playing together, and then been bombarded with similar content of it on various social media? I am sure that there were also times when Google predicted the rest of your sentence, Netflix recommended the perfect show for you, or Facebook suggested the account of an acquaintance to add as a friend on their platform. It can be confusing to think about how accurate these companies are in predicting what you are looking for or would like to see. So, how does it happen? The answer lies in data science and the information they gather.
The data science that we know today would have been impossible 30 years ago, because of the slow internet connection and the simple programming languages used at the time. However, now it is one of the most essential parts of any industry, and it is all thanks to technological advancements. Because of inventions like smartphones, tablets, mobile networks, and WiFi, the production of data keeps growing more each day. According to recent studies, 60% of the world’s population is now online, therefore, by the end of 2021, the total data in the world is expected to reach 74 zettabytes.
Now that we have established the fact that there is a lot of data online, let’s talk about the science that uses these units of information and the people who do the job. What is data science? What does a data scientist do? Read on to get the answers, and learn more about the profession of a data scientist.
What Is Data Science?
Data science is the area of study that combines various tools, algorithms, and machine learning principles with the objective to find unseen patterns, derive meaningful information, make business decisions, and build predictive models. It gathers data from numerous sources in various formats, and the way it extracts value from them is by incorporating multiple fields such as data analysis, statistics, scientific methods, and artificial intelligence (AI).
Applications of data science
Data science is a very broad term, and it has many applications. To understand the importance of being a data scientist, let’s have a look at some of the many fields which use data science:
Healthcare is one of the fields where data science has found application. Let’s learn more about it.
Interpreting medical images
Data science can be used to interpret medical images like MRIs, X-rays, and other types of images. It can also identify patterns in them, thus detecting abnormalities like tumors.
Data science can be used to model simulations that simplify the prediction of drug experiment outcomes. Some techniques are also used to predict the potential side effects of specific chemical combinations.
Data science uses the patient’s data and clinical notes to find correlations and make accurate predictions about potential diseases.
Data science is applied even in the marketing field. Let’s see how helpful it can be.
Data science is used to match the preferences of a customer with products they might like.
Predicting customer behavior
Data science is used to analyze correlations of a customer’s purchases so the company can predict future purchases that customers might do.
Data science is used to target the right people at the right time. By analyzing data, the company knows what is on-trend, how to present their products so they are appealing to people, and who is most likely to engage with the content.
Finance is another field where data science can be applied. Let’s see how.
Data science helps machines adapt to normal patterns, and then that makes it easy for them to detect any pattern of fraud transactions.
What Does a Data Scientist Do?
To simply put it, a data scientist’s job description includes analyzing data for insight. They work closely with businesses to extract their data, analyze it, and share the insight so the business can use that insight to better understand their customers. Data scientists use algorithms and create predictive models to conduct analyses.
But, what do data scientists do exactly? What are some data scientist responsibilities they have to fulfill on their job? On a day-to-day basis, data scientists deal with:
- Pulling, merging, and analyzing data.
- Using data to look for patterns or trends.
- Developing models which can detect a change in normal behavior, therefore noticing anomalies.
- Using a variety of tools, such as Python, Hibe, Excel, Tableau, Matlab, PySpark, Hadoop, SQL, and SAS to explore, model, and visualize data.
- Developing and testing new algorithms which will simplify data problems.
- Developing statistical models which can be used for predictions.
- Building data visualizations.
- Writing the results of their work, communicating, and collaborating with other data scientists to enhance performance.
- PerformING tasks as assigned by their seniors on the job, the head of the department, the chief, or the employer.
Data Scientist Qualifications and Skills
Data scientists are highly qualified and skilled people. They possess many technical and non-technical abilities which are necessary for the job. If you are thinking of pursuing a career in data science, have a look at some of the qualifications and skills you must obtain in order to fulfill the data scientist role.
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- Education – data scientists have to be highly educated. Generally, data scientists have a Bachelor’s degree in data science or a computer-related field. Many data scientists have Master’s degrees, with 38% having earned a PhD. Except for the degree, many data scientists also undertake online training to develop certain skills.
- R-Programming – data scientists should have in-depth knowledge of an analytical tool. R-programming is designed specifically for data science, therefore it is recommended for any data scientist to be skilled in it.
- Python Coding – according to a survey, over 40% of data scientists use python coding for their work. Many also use SQL coding.
For non-technical skills, data scientists should be curious and innovative. They should have good communication skills and be willing to work with a team.
Data Scientist Salary
The demand for data scientists in the market is still very high. Following the basic law of economics, when the demand is high, but the percentage of workers in data science is low then the salaries are high.
However, the salary of a data scientist still varies depending on the employees’:
- Job title
- The company they work for
The average salary for data scientists in the United States is:
- Entry-level $85.000/a year
- Early career(1-4 years of work) $95.000/per year
- Mid-career(5-9 years of work) $110.000/per year
- Late career(10-19 years of work) $122.000/per year
- Experienced(20+ years of work) $137.000/per year
In this day and age, the job of a data scientist is highly sought-after, considering the amount of data that is produced every day. Therefore, if you were considering it, this is your sign. This Is the best time to break into data science.