Things You Should Know Before Starting Your Career As A Data Scientist

By Tech-Act    
11/03/2020  428 Views

Things You Should Know Before Starting Your Career As A Data Scientist

In the recent times, there has been a lot of buzz about data science as it offers a very interesting job role & at the same time it is also very rewarding. Data science professionals are very much in-demand. They are highly paid and their job roles have a direct impact on business. Data science is used in various industries right from consumer behavior analytics in retail and e-commerce to computer vision application for detection and classification of objects and human. Hence, data science is everywhere right now and it’s going to be very exciting to witness its further evolution in future, because when we talk about data science and artificial intelligence our journey has just begun.

Well, in this blog we have listed the crucial things you should know before you start your career as a data scientist. Check out the below pointers.


1. Technical Skills are very essential: The technical skills which are very important for any data scientist are analyzing statistics, processing, computing frameworks, examining facts & doing data structuring from the large volume of information. Hence, it is required that one should have a good hold on math, programming & statistics. Along with the required skill set, one should also have relevant educational background. The educational qualification required is Ph.D. and Masters in computer science, engineering or statistics. This qualification builds a potent foundation for data scientist which helps them in understanding the technical aspects in the designated field. Let’s have a detailed look at some of the skills which data scientist need to learn.

  • Programming: Data scientist must learn coding languages which will assist them in organizing and analyzing the sets of data. The most preferred programming language in this field are Perl, C/C++, SQL, JAVA.
  • Analytical Tools: In order to extract the valuable & in-depth understanding from the organized & analyzed data, it is mandatory to possess knowledge on analytical tools. SAS, R, Hadoop, Spark & Hive are the commonly used data scrutiny tools. Data scientist must also take up some good online certifications as this will further strengthen their knowledge and skills.
  • Machine Learning and Artificial Intelligence: Latest surveys revealed that handful of data scientist have expertise on advanced machine learning. There are few skills which every data professionals should know i.e. Survival Analysis, Computer Vision, Time series, Outlier Detection, Natural Language processing, Recommendation Engines, Reinforcement and Adversarial Learning, Supervised and Unsupervised ML. These skills will make you more efficient and effective while solving the various data science issues.

2. Non-Technical Skills: In every field apart from the technical skills, educational qualification and certificates, there are more qualities required which makes you a great professional. Well even when I talk about data scientist, there are few non-technical skills which they need to develop that will further intensify their value in the industry. Let’s take a quick look at these non-technical skills.

    • Communication Skills: As a data scientist you would be analyzing the data and will draw logical conclusions and then you will be communicating with all the key stakeholders and explaining them that why these data points are important. Hence, it is essential that data scientist should possess strong communication skills so that he/she is able to convey his/her opinions & ideology across the organization and especially to the ones who are not from the technical background. Additionally, there will be a lot of communication that will take place internally and externally via emails for which we can use tools like CrowdWriter and Grammarly as this will help in producing error free report. It is suggested that data scientist should build some story around their data as this will not only make it interesting but it will also become easy for everyone to understand. In this way, data scientist can easily share & convey the findings with all the employees.
    • Awareness about Business: As a data scientist your findings and inferences have direct impact on the business. Therefore, it is very important that you keep yourself updated about the changes that are happening internally and externally. If you do not have business awareness then your technical skills will be unproductive. Being aware about the business, will help you in identifying if there is any upcoming risk and accordingly it can be tackled so that the organizations growth & sustainability is maintained.

Teamwork: You simply can’t function solo. As a data scientist, you will have to collaborate with company executives, designers & product managers to achieve better results. You will have to get involved with marketing managers to launch the campaigns. You will have to work with developers and clients to create data pipeline and to boost the workflow. Hence, it is important to be a good team player as you would end up working with almost every department in the organization.

3. Education: If you are aiming to become a data scientist then you will have to pay immense attention towards your academics. Data scientists are highly qualified professionals. More than 75% of them are either Ph.D or Masters. Majority of them have degree in Computing Science, Statistics, Mathematics, Engineering or Social Science. You can also take up some online certifications to further enhance your skills.

Few Tips:

  • Trust me data science is not a cake walk, so if you have learning attitude only then you will be able to enjoy this adventurous role of data scientist.
  • It is important to ask questions and raise issues about your data because your majority of the time will be consumed in analyzing it.
  • Participate in competitions on Kaggle, as it will further motivate you and will improve your prediction level.
  • As a new blood start learning with some free stuff like Intro to Data Science, Machine Learning & Kaggle Learning path.

Summary:


“I have no special talent. I am only passionately curious” said by Alert Einstein. Well it only means that if you want to be successful in your chosen path then you should never let the curiosity die. It is important to be curious, the more curious you are the more questions you ask, the more questions you ask the more you end up learning. And only continuous learning guarantees success.

So stay focused and you will achieve your goal!


In the recent times, there has been a lot of buzz about data science as it offers a very interesting job role & at the same time it is also very rewarding. Data science professionals are very much in-demand. They are highly paid and their job roles have a direct impact on business. Data science is used in various industries right from consumer behavior analytics in retail and e-commerce to computer vision application for detection and classification of objects and human. Hence, data science is everywhere right now and it’s going to be very exciting to witness its further evolution in future, because when we talk about data science and artificial intelligence our journey has just begun.

Well, in this blog we have listed the crucial things you should know before you start your career as a data scientist. Check out the below pointers.


1. Technical Skills are very essential: The technical skills which are very important for any data scientist are analyzing statistics, processing, computing frameworks, examining facts & doing data structuring from the large volume of information. Hence, it is required that one should have a good hold on math, programming & statistics. Along with the required skill set, one should also have relevant educational background. The educational qualification required is Ph.D. and Masters in computer science, engineering or statistics. This qualification builds a potent foundation for data scientist which helps them in understanding the technical aspects in the designated field. Let’s have a detailed look at some of the skills which data scientist need to learn.

  • Programming: Data scientist must learn coding languages which will assist them in organizing and analyzing the sets of data. The most preferred programming language in this field are Perl, C/C++, SQL, JAVA.
  • Analytical Tools: In order to extract the valuable & in-depth understanding from the organized & analyzed data, it is mandatory to possess knowledge on analytical tools. SAS, R, Hadoop, Spark & Hive are the commonly used data scrutiny tools. Data scientist must also take up some good online certifications as this will further strengthen their knowledge and skills.
  • Machine Learning and Artificial Intelligence: Latest surveys revealed that handful of data scientist have expertise on advanced machine learning. There are few skills which every data professionals should know i.e. Survival Analysis, Computer Vision, Time series, Outlier Detection, Natural Language processing, Recommendation Engines, Reinforcement and Adversarial Learning, Supervised and Unsupervised ML. These skills will make you more efficient and effective while solving the various data science issues.

2. Non-Technical Skills: In every field apart from the technical skills, educational qualification and certificates, there are more qualities required which makes you a great professional. Well even when I talk about data scientist, there are few non-technical skills which they need to develop that will further intensify their value in the industry. Let’s take a quick look at these non-technical skills.

    • Communication Skills: As a data scientist you would be analyzing the data and will draw logical conclusions and then you will be communicating with all the key stakeholders and explaining them that why these data points are important. Hence, it is essential that data scientist should possess strong communication skills so that he/she is able to convey his/her opinions & ideology across the organization and especially to the ones who are not from the technical background. Additionally, there will be a lot of communication that will take place internally and externally via emails for which we can use tools like CrowdWriter and Grammarly as this will help in producing error free report. It is suggested that data scientist should build some story around their data as this will not only make it interesting but it will also become easy for everyone to understand. In this way, data scientist can easily share & convey the findings with all the employees.
    • Awareness about Business: As a data scientist your findings and inferences have direct impact on the business. Therefore, it is very important that you keep yourself updated about the changes that are happening internally and externally. If you do not have business awareness then your technical skills will be unproductive. Being aware about the business, will help you in identifying if there is any upcoming risk and accordingly it can be tackled so that the organizations growth & sustainability is maintained.

Teamwork: You simply can’t function solo. As a data scientist, you will have to collaborate with company executives, designers & product managers to achieve better results. You will have to get involved with marketing managers to launch the campaigns. You will have to work with developers and clients to create data pipeline and to boost the workflow. Hence, it is important to be a good team player as you would end up working with almost every department in the organization.

3. Education: If you are aiming to become a data scientist then you will have to pay immense attention towards your academics. Data scientists are highly qualified professionals. More than 75% of them are either Ph.D or Masters. Majority of them have degree in Computing Science, Statistics, Mathematics, Engineering or Social Science. You can also take up some online certifications to further enhance your skills.

Few Tips:

  • Trust me data science is not a cake walk, so if you have learning attitude only then you will be able to enjoy this adventurous role of data scientist.
  • It is important to ask questions and raise issues about your data because your majority of the time will be consumed in analyzing it.
  • Participate in competitions on Kaggle, as it will further motivate you and will improve your prediction level.
  • As a new blood start learning with some free stuff like Intro to Data Science, Machine Learning & Kaggle Learning path.

Summary:


“I have no special talent. I am only passionately curious” said by Alert Einstein. Well it only means that if you want to be successful in your chosen path then you should never let the curiosity die. It is important to be curious, the more curious you are the more questions you ask, the more questions you ask the more you end up learning. And only continuous learning guarantees success.

So stay focused and you will achieve your goal!



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