A decade ago, many jobs in the IT industry did not exist. With more and more businesses becoming interested in data and understanding its value, new jobs are created. One of these is the role of a data scientist. Data scientists are seen as analytical data experts who specialize in both the business and IT worlds. Today, they’re highly sought-after, well-paid and in constant demand.
But what exactly does a data scientist do? Data and specifically big data is a virtual gold mine for businesses. It offers plenty of insights that can be used to tailor business systems and processes to increase revenue. Not everyone can analyze data, and this is where a data scientist comes in. Businesses can hire data scientists to gather, sort and analyze large sets of data to gain insights from it. The data scientists can then offer valuable observations and advice to a business.
Data science is a relatively new concept and the role of a data scientist is still evolving. However, a certain skill set is required for a data scientist to be able to operate today. Let’s look at which skills a data scientist should have:
Skills Every Data Scientists Should Have
Data scientists help businesses to make sense of their data. For them to work effectively they have to have a certain set of skills. Typically, a data scientist should have an educational background in the technical and IT fields and be an analytical thinker. Being an analytical thinker requires one to be observant, to be able to take an in-depth look at certain things and to always think about possible solutions for problems.
Furthermore, data scientists have to communicate complex insights and ideas. Therefore, they have to be able to communicate efficiently and effectively. A data scientist should ideally also be a great leader and an excellent team player, as the job requires them to constantly engage with others.
Other skills include:
- Data Visualization
- Statistical Analysis
- Risk Analysis
- Machine Learning Techniques
- Software Engineering
- Data Mining
- Cloud Tools
The top data scientists in the industry have many years of experience and have worked on several big projects alongside other teams, including operations, marketing and customer service. Deciding to hire a data scientist requires a business to take into account the complexity of the work that needs to be done. This will indicate the experience the candidate should have. Data scientists’ salaries depend heavily on the amount of experience they have. Let’s look at the average salaries of data scientists today:
Average Salaries of Data Scientists
Data scientists play an important part in businesses operations and if they work effectively, they can take a business to new heights and improve success in the future. Because of its value, data science is often quite costly for a business. However, when looking at the advantages a data scientists can bring to a business, spending the money is a no brainer. A data scientist will offer an excellent return on investment.
According to Glassdoor, the average salary of a data scientist is $113,436 or $9453 per month. However, it is much lower in certain countries. The salary also depends on the background, skill and experience a data scientist have. Top candidates are more experienced and the salary for some of the best scientists can go up to $163,500.
Data scientists can also be hired remotely and per hour, which can lower the cost greatly. According to salary.com, the average hourly rate for a data scientist is $27 and $32. This can be a more cost-effective option for smaller businesses as candidates can be hired if and when needed.
From this, it is evident that any business can invest in data science, as the salary levels cater to most businesses’ budgets.
Where to Find Data Scientists for Hire
Data scientists are becoming more popular. More and more individuals are opting to study in the field because of the position’s high demand and excellent salary offering. The question many businesses ask now is where to find the perfect data scientist candidate.
Many data scientists no longer opt for full-time employment, but rather work on a freelance or remote basis. This makes it somewhat easier to find the ideal candidates. Outsourcing companies are an excellent place to start. These companies usually take care of the hiring process of freelance data scientists and can advise on the best solutions for specific needs. Such a company will also take care of the contracts. This makes the hiring process easier and a business can rest assured that they are investing in the best person for the job.
Why the Demand for Data Scientists Is High
As mentioned before, data scientists are in high demand. Let’s take an in-depth look at why:
Data is playing an increasingly bigger role in the business world today. Many top companies are using it to their advantage to tailor certain aspects of their operations to offer better products, services and customer support. Smaller businesses are also now coming on board as they realize that not exploring the field can put them on the back foot. But they cannot analyze the data on their own. To stay relevant and to move forward in today’s competitive business world, businesses have to hire experts.
How does the future look?
From monitoring web traffic to predicting future trends, data is only becoming a bigger part of the business world. This means that the demand for data scientists will only grow going forward. It is predicted that data science will eventually become absolutely necessary and that every business, big or small, would hire data scientists in the future.
The Bottom Line
Any business who wants to improve their operations has to invest in the proper analyzing of data. Business who are interested in this should look into hiring a data scientists specialist. Such an expert has experience in the field and can offer the right skills to assist a business to gather, sort and analyze structured and unstructured sets of data effectively. From this, it is evident that businesses can no longer afford not to hire data scientists for a successful business in the future.