5 Rare Data Science Skills That Can Help You Get Employed

Data science skills are predominant to shine in as a data scientist and build effective ML models. As a data scientist, you need to have coding, marketing, visualization, and analytical skills to outperform.

Data Science skills: Undoubtedly, data science is a booming career today. Many companies are hiring data science experts to use their past data and create models. These models will predict pricing, temperature, who has a chance of getting promotion and so on.

No matter what the use case, data science will help you create models. To become a data scientist, you need to have excellent Data Science Skills such as Python, Hadoop, data visualization skills, and many other libraries. However, apart from this, some rare skills make you stand out from others.

You have to enroll for the data science course at Physical Wallah to excel in data science skills. The course is online and you can learn at your own pace. It is also available at a 22% discounted price. You can enroll for the course and have access to 7 real-time projects. After the course, you have to pass the assessment to get a valuable certification that can fetch you a job and make your resume stand out from others.

Apart from coding skills, you also need to have some rare skills that make you a proficient data scientist compared to others in the job market. To learn about those rare skills, read this article. However, to know rare skills for a data scientist to flourish, read this article.

Also read: What is Data Science?

Table of Contents

Rare Data Science Skills You Need to Become a Data Scientist

The following are the rare skills you need to have to become a data scientist:

Model Visualization

Data scientists used to work alone without any dependencies on others. They used to create the models showing up the predictions on the historic dataset using Data science skills. These used to be passed to the C-level executives in the company to understand the predictions and make appropriate business decisions.

Now, companies want to understand the data science outputs in detail. It is a must for data scientists to explain what the model does, how it works and why they choose that target column to make predictions.

You can work with the visualization team to show the predictions visually in the form of a bar or pie chart with Data science skills. For instance, you have come up with a model that can predict the churn of telecom companies. Instead of showing the code to them, it is good to show the bar charts that explain the model and the predictions.

You can segment the customers and find out the areas where they have a high chance of increasing the number of customers. The model is transparent and easier for even non-technical savvy to understand. It is one of the great Data Science Skills to explain the model through the code you have written, but you need to use flowchart tools to explain the decision tree while explaining the code to a non-data scientist or a non-coder.

Also read: 30 Best Data Science Books to Read in 2024

Feature Engineering

It is the most important Data Science Skills and tool the aspiring data scientist should have. You can learn a bit about this in the data science course. However, you need to identify the features that can have an impact on creating a precise model.

In addition, you can use this model to make predictions accurately. The data scientists give high priority to model algorithms. They use the best algorithms to create models using historical data.

Priority should be given to features in the data. When you identify the correlated features to the target feature, you can make a powerful model. With feature engineering, you can select, modify, and create features that boost the performance of ML models.

For instance, when you are developing a model to predict real-estate prices in different locations, it is necessary to take features like bedrooms, square feet, and location into consideration. These all factors decide the pricing. Using feature engineering, these features are considered for price prediction. You must calculate the closest transportation station or come up with a feature that can show the property’s age. You can combine these features with new ones. The new features you must consider are crime rate, ratings of schools and amenities around.

It is one of the rare Data science skills that every data scientist should have to become successful in this area of job. They are technically sound, but they also need to have domain knowledge. This helps them predict better, creating effective ML models.

You have to have the right data in hand and transform this data into an informative piece. Using this informative piece, you can test and train the models. The machine learning courses impart extensive knowledge of feature engineering to students. Learning this one of the most in-demand data science skills will be an add-on for every student.

They can excel in this area and can build models that give accurate predictions on any data. You also have to work on the real-time data to use your feature engineering strategies. This helps you strengthen your skills.

Learn About Data Governance

Data governance is a must for data scientists. When you are provided with the patient data and asked to come up with a model that can predict the patients who are at risk of some diseases. Then the biggest challenge that every data scientist faces is developing effective models. However, not just this the model should also be ethical and sustainable.

You have to make sure that the data you gathered for modeling is compliant with HIPAA and GDPR rules. However, you have to meet this compliance in case you are taking the data from the locations where these rules are stringent. You need to know whether you have the authority to use this data legally. In case you have that authority, you must keep this anonymous. It is a must for you to take consent from patients.

Apart from these Data Science Skills, you should also do the documentation of the code, data transformations you have used and models you have generated. This helps even a non-expert user to understand what you have done on that dataset. You must have traceability to stay compliant for future audits too.

Ethics

If you are a data scientist, you must be familiar with data scientist skills and responsibilities. Apart from knowing how to create models, you should also be ethical. The models you create from the data should not evoke biases among other groups. Your models should treat all segments in the dataset equally. There is a big company which has come up with the recruitment model.

Using this model, the HR team can pick the potential candidates from a group of resumes and start to conduct interviews for them. The models are trained on the resumes of candidates. All these are male-dominated. The model they have developed is favoring male hires.

All the resumes it picked are males instead of data science skills and tools. Therefore, this model is completely unethical.

The data scientist is a good decision-maker. The decisions a data scientist makes will have a huge impact on people. You cannot be ignorant. Whenever you are creating a model from the dataset with Data science skills, you must perform data transformations and segmentations properly.

Without which a lot of repercussions arise. You have to think a lot about which transforms to apply and which data to pick. This helps you bring up a model that is useful for all.

Also read: Top Data Science Courses In 2024

Marketing

You should know how to market your skills. The better you market your achievements, projects and skills, the faster you get the job. When your data science skills resume looks rich, companies will shortlist you for interviews. They will consider allowing you to prove it.

This is all possible only when you have good marketing skills. If you sell your resume, you can attract the interviewer and grab a high-paying job. In data science, you should be able to explain what models you have built and be able to explain those clearly. No matter how good the model is, if you do not have good convincing and marketing skills all efforts go into vain. For instance, if you have come up with a model that can predict equipment failure. This model helps you to do frequent maintenance to avoid equipment failure in manufacturing plants.

Using this model, you can save a lot of money in avoiding the equipment to have increased downtime. In case you cannot explain this to the C-level executives, the model you developed won’t be of any use.

Having good soft skills for data scientist lets people explain the model clearly. You must be good at convincing and impressing the interviewers.

Having skills required for data scientist fresher also helps you to let people know how useful the model you developed is. You can prepare a presentation and highlight how your model can save a huge amount of the company’s money.

The model you develop should also improve productivity and should give long-term benefits. All these should be explained in the presentation without missing any point. If you can’t sell your achievements no one can better do it for you.

It is one among the rare Data science skills that is not taught anywhere but should be inculcated by yourself. Many data scientists lack this. In case you have this, you can make a difference in the company and in winning the interview.

The data scientists just work towards building an accurate model and fail to explain how it works. The real advantage of the market can be taken only when you market yourself. There are courses available to learn marketing yourself.

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Data Science Skills by Category

You might be wondering what are the primary skills one should have to become a data scientist. The table below will give you a quick glimpse of skills required to excel in the data science field.

Data Science Skills segregated by the category
S.no	Skill	Category
1.	Python	Programming language
2.	Data visualization	Business & communication
3.	Probability & Statistics	Math & Stats
4.	Critical thinking	Business & communication
5.	Communication skill	Business & communication
6.	SQL	SQL databases or other databases
7.	Excel	Business & Communication
8.	Github	Software development
9.	Machine learning techniques	Data science & ML tools

Is a Career in Data Science Right for you?

Data science is a shining field currently. Many people are undergoing data science courses in top institutes to crack the job of a data scientist.

If you are bent on building a rewarding career in data science, you can find the best data science course at Physics Wallah. Going through this course at your pace will help you understand the concepts in-depth. You can always go back and listen to the videos if you find it hard to perceive any topic.

You must go above the technical Data science skills to stand out in the job market. Enroll for the data science course today! Get acquainted with technical skills, ethics, data governance and marketing skills through this course.

Also read: What Is the Importance of Statistics for Data Science in 2024?

FAQs

How to have a fulfilling career in data science?

You can have a great career in data science when you keep brushing up your technical skills and rare data scientist skills like marketing yourself, doing better feature engineering and learning some visualization tools.

Why is there a huge demand for data science professionals?

There is a lot of data churning out every day and a lot of problems to be solved with data. Not many are talented enough to build great models. However, you can only have demand only when you have good technical and rare skills.

How should data scientists prepare for interviews?

You can only crack the interview if you prepare rigorously. You also need to market your resume and show interesting data science projects you worked on. You must build a profile doing a lot of projects and circulate your resume in your circle.

What top algorithms that data scientists will use in building models?

Machine learning enthusiasts should understand different algorithms to use. These are what is required to build models. The popular ones include logistic regression, naive Bayes, support vector machines and random forest.

What are the most valuable Data science skills that a data scientist should have?

Data scientists are hired by all industries to work on their data and come up with models. The common Data science skills they should have are coding skills, analyzing the data, and knowledge of Tableau and Hadoop knowledge.