Have you ever wondered how much data we create every day?

Cost Analysis Breakdown for Hiring Data Scientists

The answer is “a lot”.

As per Statista, in the year 2020, over 306.4 billion emails were estimated to have been sent and received each day, and it is estimated to grow over 376.4 billion daily emails by 2025. This data is just for email sent and received, and it is impossible even to imagine just how much data is being created every day from around the world on different platforms. This is the reason why we have summed up our answer with just “a lot”.

However, this proliferation of data can become one of the driving forces behind the success of your company. This means a vast number of facts and untold nuggets of information in data can be used to make better business decisions. But how do you get the required information out of this unstructured and unorganized collection of data?

The answer is “Data Scientists”.

Why hire data scientists?

Data scientists help businesses analyze collected data and make sense of it. They are armed with methodologies to control the noise in the data and offer potential conclusions to issues your company is facing or might face in the near future. Hence they are needed in a wide range of industries, ranging from healthcare and automotive to science and research.

Given their demand and cutthroat competition among various companies from different industries have made it quite difficult for hiring managers to hire a highly-skilled data scientist. Some companies have an entire team of in-house data scientists, but not all can afford this option. But a sure-shot way to ensure you hire an experienced, skilled, and affordable data scientist is remote recruiting.

However, before you make any decision on how to hire, first take a look at the benefits of having data scientists in your team –

  • Helps the management in making better decisions – Data scientists are trained to handle uncertainties that facilitate the improved decision-making process. They communicate and demonstrate the value of data collected and analyzed for the company’s success.
  • Define organizational goals – The data analysis helps companies improve their performance by providing the stakeholders with a solution to better customer engagement and satisfaction, resulting in increased revenue generation.
  • Helps in identifying opportunities – Identifying new opportunities for the company’s success is not an easy task. But, Data scientists excel at questioning existing methods and making assumptions to develop better processes.
  • Identifying the target audience – All businesses have at least one source of customer data that is stored. It is crucial to identify demographics that can help in finding potential customers. Data scientists help in identifying potential customers through data analysis.

Skills to look for when hiring data scientists

Here is a comprehensive list of qualities that you should consider when you hire data scientists –

  • Data intuition – Having a degree or certification in data science does not ensure that the candidate has data intuition as well. This is why you should make sure that the candidate is excellent at identifying patterns within sets of structured and unstructured data. You can do so by asking them a quick data visualization question.
  • Creativity – It is an essential quality as it helps them use their knowledge to solve real-world problems. Data scientists should find new opportunities that can provide new insights for the company’s gain.
  • Technical skills – Python coding, data visualization, artificial intelligence, machine learning, Hadoop, and databases are must-have skills that every data scientist must have in their arsenal.
  • Statistical thinking – Since statistics is the discipline that offers tools and techniques to find patterns and give insights into data. It is one of the most crucial and fundamental skills for a data scientist.
  • Communication skills – A good data scientist should communicate the right problem statement to the stakeholders. That, in turn, can help in making better decisions that can help in improving the profits.

Data scientist salary

Data scientists salary depends on three key factors –

  • Experience – The more the experience, the better the pay. People with more experience in data science and analytics get paid more than those who have less experience.
  • Academic achievement – In simpler terms, people with PhDs get more paid than people with just a bachelor’s degree.
  • Company size – Companies such as small start-ups usually pay less than the industry average.

According to payscale, the average salary of a data scientist in the USA is $136,614 / year.

Data scientist responsibilities and qualifications

Here is the data scientist job requirement or responsibilities that you should be mindful of during the recruitment process –

Data scientist roles and responsibilities

  • Participating in the software development process to provide data-driven architectural solutions for multi-product, multi-project, and multi-industry portfolios.
  • Working with stakeholders to find new opportunities to leverage profitable business solutions.
  • Mining and analyzing data to improve marketing techniques and business strategies.
  • Assessing the effectiveness and accuracy of new data collected to ensure the company is using the right data gathering techniques.
  • Using predictive modeling to predict any uncertainties and provide solutions for them.
  • Data analysis to improve customer experiences, revenue generation, ad targeting, and other business outcomes.
  • Coordinating with other departments to implement models that can bring better results.
  • Monitoring the outcomes of different models implemented for better performance.

Data scientist qualifications

  • Experience in programming languages such as Python, R programming, etc.
  • Experience in creating data architectures.
  • Understanding of various machine learning techniques.
  • Knowledge of a variety of statistical techniques and concepts.
  • Excellent communication skills.
  • A drive to learn new techniques and technologies.


Now that you know why you should hire data scientists and what skills to look for when recruiting, you should also ensure that you are not going over budget. With a sharp rise in data scientists’ salaries, it can be challenging to find an in-house data scientist who is highly skilled and affordable. However, remote data scientists are making this job a lot easier. Remote hiring ensures that you hire an experienced and highly qualified data scientist for your data science requirements.

Author Bio –

Anupriya Singh

Anupriya is a content writer who is passionate about writing on a variety of topics. When not writing, you can find her reading or sketching.