How to Hire a Data Scientist? Qualities Every Data Scientist Must-Have

Currently, data science is one of the trendiest job careers. The moment businesses realize its importance in their operations; the demand increases worldwide. In many companies’ data science professionals are the foundation that helps organizations in analytics, NLP, ML, AI, and other areas.

Data science is the power that enables organizations and stakeholders to make informed decisions and solve their problems. Due to that, the pay scale for data science is relatively decent, one of the attractive elements that gravitate individuals towards this field. So, the demand increased, and it became an exciting career option for professionals and students.

However, it includes those who need to be certified but are willing to play with data and have questions about what qualities are essential to ace a data scientist career.

Qualities Must Have in Data Scientist

Like most successful careers and desired advanced positions, the more fabulous suite of skills you will need to become successful. Thus, there are certain qualities that data science professionals should have to be proficient in their role.

1. Statistical Thinking

Data scientists are professionals who can turn their data into information. Hence statistical knowledge is at the forefront of the toolkit. The leading task of data science experts is knowing algorithms, how and when to apply them correctly, and get the desired outcome.

A good data scientist can extract helpful insight from any data by implementing algorithms to make informed predictions and recommendations. Also, the experts can sense something fishy instantly and ask questions directly to stakeholders before retreating to the code cave. It enables them to make a difference between game-changing insight and costly blind hunch.

2. Data-Driven Decision Making

A good data scientist will only judge, conclude and make a decision with accurate data. Scientists should decide their approaches to business problems and other things like what tools and techniques are needed to visualize and communicate in the best possible manner. Think like a curious child and explore the surroundings to arrive at a reliable conclusion.

3. Strong Command Over Programming Language

You need to know programming to make sense. You won't be able to execute any tasks that will give you insights. To become a data scientist expert, you must be proficient in R and Python. Some popular languages such as Java, SQL, and MATLAB are also required to learn. But, there is a solution: you can avail of data scientist certification because, in the courses, you get the excellent opportunity to learn all the programming languages, which is essential.

4. Teamwork Skills

Data science is often a team sport. Each member brings their expertise to the problem. To create data pipelines, data scientists must communicate well with analysts and engineers. They also need to communicate with other team members that will use their results in some way. Data scientists need communication skills because they often work with non-technical people and must clearly explain complex ideas.

5. Data Wrangling

Every organization needs more data or is available in an unstructured format. Due to this, it is crucial to understand how to streamline the data errors in the dataset. Sometimes the corrupted data may miss some valuable insight or may need to be in a structured format. Thus, you can quickly eliminate damaged data and sort it using data wrangling. However, one of the significant abilities of a data scientist professional is the ability to process and use data for analytics.

6. Quantitative Analysis

This is the core of what a data scientist does. A data scientist's job description includes a visceral and calculated understanding of complex environments and their behavior, creating prototypes and models to test hypotheses, and munging messy data to develop models and prototypes. You must know how to build predictive and regression models, Machine Learning - both supervised and unsupervised learning algorithms.

7. Technical Acumen

Data scientists write code and work in groups to produce tools, packages, modules, features, dashboards, websites, pipelines, and many more. A great data scientist has the spirit of an ethical hacker. In this field, technical flexibility is crucial because the gold standards change at an alarming rate. The professionals work collectively and share their experience and knowledge to ensure they can effectively fulfill client demands. If your data scientist is a quick study, you made a sound investment decision.

How to Hire Data Scientist?

There are various ways to hire the best data scientist for the job profile in your organization. But, at present, data scientists are much more complicated to recruit than traditional IT roles because they are highly skilled and know to make decisions based on data–driven insights.

However, a data science career is a hot topic, and there need to be more people with the required skill set to fill the vacancy. Thus, you must act fast if you are looking for the right applicant to fill the position. Therefore, to achieve your goals, there are a few principles that are important to include in the hiring process:

• Design the process and ensure the applicant is sold on continuing the cycle.

• Move quickly

• The hiring process is transparent, so it clearly shows the applicants about hiring needs.

• Take decision collectively

• Conduct objective evaluation to remove biases.

This process is not created on guesswork but based on the hiring process in general, and thorough consideration is taken to improve the whole process.

Conclusion

Data scientists are responsible for making the data valuable for the company. The only way to do this is to find insights that can convert into actionable, quantifiable items that can track with metrics. Your organization will be proud to champion data-driven decisions.