The demand for cloud computing engineers keeps growing. This trend specially is in uprise for the data scientists. This high demand is making companies look for data scientists to become a part of their organization. A recent analysis on hiring trends has shown that there are more than 3000 data science job postings across various job portals. Machine learning and data science opportunities are humongous in the United States and need for it is steadily increasing across the world. Many companies have amped up their use for data science. US Bureau of Labor Statistics Job Outlook report predicts an enormous growth of data engineers in the upcoming decade. According to experts, data science skills are the future of the analytics engine.
Data is important for every company and useful input for domains. Organizations harness this data to achieve strategic goals. To get valuable insights into data, companies have to perform data analysis. So, a data scientist can be well-compensated for their skills.
To understand how data scientists are in demand and what is their role, we have conducted our own research. We will talk about the insights from our public job portal and learn about what do corporations or startups have to look for in candidates.
Who are Data Scientists?
A data scientist can transform raw data into meaningful information that businesses can use to work better. All organizations collect a large amount of data for every operation. As a data scientist, one has to solve the problems businesses might be facing with imaginative and innovative methods.
Using a web scraping service for faster data mining along with machine learning helps data scientists to have simplified data and build solutions. Predicting data helps in explaining an analysis in simple language. Data scientists are greatly in demand across various sectors since businesses need a combination of analytical, technical, and communication skills.
High Demand Industries for Data Scientists
Data scientists are required across multiple domains, including-
- Government
- Finances
- Health
- Academia
- Retail
- Scientific research
- Ecommerce
- Information technology
Top Tools Data Scientists Need
Data scientists need tools to analyze and process the collected data. Your organization might have reservations when it comes to the tool but knowing different tools is an important qualification for data scientists. As per our analysis of the job postings, 91.5% include specific tools for a data scientist job. So, here are the top tools that a data scientist should be able to use
- Cloud
- Python
- R
- SQL
- Spark
- Amazon Web Service
- Java
- TensorFlow
- PyTorch
- Tableau
Data scientists are required to be adept at different programming languages. One of the most popular languages known to data scientists is Python and 61% of the job descriptions include it. The only reason behind this is it is a powerful but simple language. So, Python should be a good starting point if you are looking to hire a data scientist.
Another language that is popular with job postings is SQL, as 46% of the job postings mention it. Many businesses are now using SQL-driven databases for storing their data. If your company is using it too, it is a good idea to look for candidates who know classic database SQL language.
Cloud has also become popular in recent times. With time, more and more companies are moving to the cloud platforms. Data scientists can tap into the different functionalities of the cloud, such as computing power or data storage. One of the most well-known cloud providers is Amazon Web Services.
R has a robust academic background, and the many new statistical models are often implemented using R. 37% of the job descriptions also mention R and it is taken to be the competitor of Python.
Spark and Tableau are also in great demand. They can be useful if your company has a large amount of data. The former offers an interactive platform, which doesn’t require much coding. Java is valuable for some employers. It is a common programming language that is popular among engineers.
Top Data Science Skills Must for Data Scientists
Other than being good with the tools, data scientists should also have technical skills to help the company achieve its goals.
Here are the top skills you should look for when hiring a data scientist.
1. Statistics
Knowledge plays a significant role for data scientists. More than half of the job postings mention statistics as a requirement. So, a candidate should learn about probability theory, basic mathematics, experimental design, and other concepts.
2. Machine Learning
Even though machine learning is not the only thing data scientists do but 66% of job postings include it. while hiring a candidate, make sure they know algorithms, such as reinforcement learning, supervised learning, and unsupervised learning. It is a core skill to have. It is used for building predictive models. For instance, you might want to predict the total number of customers you will have in the following month by analyzing the previous month’s data, and machine learning can help with it.
3. Data Visualization
Data visualization is like art as it with it, experts build a story out of visualization. A candidate has to be familiar with plots, such as Bar Charts, Histograms, Pie Charts, and eventually move on to Thermometer Charts or Waterfall Charts. All these tend to be used for your company’s data analysis program. An analysis is much easier to understand through colorful charts.
4. Big Data
Businesses are generating quintillions of data every day. With the popularity of the internet and social media, there has been an increase in data generation. Organizations can be overwhelmed with such large volumes of data. This can be handled by using Big Data Technology to store and use data properly. Thus, it is a tool that you must master.
5. Deep Learning
Now, almost everything depends on Deep Learning, be it a self-driven car or a funny video made using deepfakes. Deep Learning is a result of advancements in data storage capabilities. To use this for your business, you must make sure that the candidate is well-versed in his programming. They should be good with mathematics and have grip on linear algebra.
6. Software Engineering
To make sure your code doesn’t wreak havoc during the production stage, you need to hire a software engineer. They should have a good grip on data types, software development projects, time-space complexity, and compilers. A clean code can help your business in the long run.
7. Data Manipulation, Analysis, and Prediction
A Data Manipulation professional can organize data in a way that can be read better. It will help you be more efficient. Data manipulation might take a lot of time, but it helps with efficient data analysis and prediction.
Data analysis is where you gain insight from the data and learn about it. Once you learn about the data, you can predict customer behavior and plan a course of action.
8. Model Development
Model development is considered to be the most underrated step in Machine Learning. After data scientists come up with an effective model for a product, it is the job of a model developer to turn a dream into a reality.
Usually, the task is performed by Machine Learning engineers, but it depends on the type of organization you run. Data scientists should have in-depth knowledge about model deployment.
Benefits of Having a Data Scientist in Your Company
Are you wondering if you need a data scientist for your business? A report released by McKinsey Global Institute predicts a successful analysis of big data can potentially improve GDP in manufacturing by as much as $325 billion by the end of the decade.
Here are a few benefits of data scientists for your company.
1. Eliminate the Risk of Your Company
Data scientists analyze client churn pattern that enables them to react proactively if they notice a trend in customers favoring your competitors over yours. With the help of a data scientist, you can evaluate data from other businesses that you are considering partnering with.
2. Understand Your Customers Better
Like everything else, your customers’ behavior also changes. But how do you monitor that? Well, with the help of a data scientist. Your data scientist can uncover actions taken by your customers and help you improve your business model.
3. Improve Forecasting
Businesses use data mining to predict outcomes in the future. Some data scientists have skills in both areas. By hiring a data scientist, you can improve forecasting.
4. Get Unique Insights
Effective data analysis will help you get better insights. In fact, they can give you unique and new insights that you might not have thought of before.
Importance of Data Science in Today’s World
Data Science is evolving to become the most important thing. When it comes to this field learning doesn’t stop. New and advanced tools are being introduced every day. So, a data scientist has to be always learning and curious. A lot of advancements wait in the field of Data Scientists.
