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The data science sector is rapidly growing and evolving. The applications of data science are found to be evolving everyday. Data scientist jobs become high in demand and it is worth entering the data science industry if you have enough proficiency in aptitude and analytical skills.
Entry-Level Data Scientist Job
Those who are aspiring to become a data scientist, there are plenty of opportunities out there. If you have a proficient mindset and enough analytical skills it is not that difficult to enter into this field. Every industry from finance to healthcare, tech to education needs skilled data scientists and hiring talented data scientists. So it is worth entering data science industry and staying for a long period. According to a study the employment rate of data science sector will increase by rate of 36% between 2021 and 2031.
In this blog post, we are covering some of the common entry level jobs in data science field. As data science field is blooming day by day there are lot of opportunities for people with a little or no experience to land into this field.
Data Scientist Intern
A data science intern is an entry level employee learning the ropes of data science practically by working with experienced data scientists. They usually work on data cleaning and preparation or statistical analysis. They might assist in developing and creating new algorithms and create models in a prototyping environment and creating visualizations to show how data is being utilized.
A data science intern should have work experience with various tools like Excel. They should be aware of programming languages like Python, R or SAS.
Junior Data Scientist
A junior data scientist will do the same work as a senior data scientist do. They usually study about how to gather data, analyze, report and communicate the result of extracted data. They differ from a Senior data scientist in that they are less likely to be involved in huge datasets and complex machine learning models.
A junior data scientist must be proficient in programming languages like Python and R. By having additional knowledge of data manipulation and familiarity with visualization tools like SQL and Tableau can give them a competitive edge.
Junior Data Analyst
A junior data analyst will grasp the fundamentals of data analysis and still learn how to apply this knowledge professionally. They usually work with senior analysts and analytical managers to learn about a variety of tools and how to interpret the data. They also assist other employees with cleaning up data and prioritizing the completion of a project more efficiently.
To be hired as a junior data analyst, you should have a strong communication skill and should be comfortable with working in a team environment. They should be aware of programming languages like R, Python, SAS/SPSS, or SQL.
Junior Database Administrator
A junior database administrator helps to manage database driven websites or applications with a limited administrative responsibility. They build new databases and tables, keep an eye on performance, and manage problems with their databases.
They need to know how to write queries in programming languages like Python or SQL. To manage the databases they should be able to use tools like SQL Management Studio or Toad.
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Junior Machine Learning Analyst
A junior machine learning analyst starts their journey by learning about different types of machine learning like supervised and unsupervised machine learning and moves towards advanced topics like neural networks. They also learn about algorithms like k-means clustering or linear regression. They will also expected to understand the valuability of data analytics and its impact on business decisions.
To be hired as a junior machine learning analyst, you should have a deep knowledge of statistics and probability. It is also valuable to have a strong understanding of linear regressions and their limitations.
Junior Data Modeler
A junior data modeler is an entry level data modeler who is responsible for generating and preserving the database structure for a company. The task of a junior data modeler includes creating tables and relationships between tables and also responsible for other various tasks like designing indexes and triggers etc.
To be hired as a Junior data modeler one should have a basic knowledge of relational databases, SQL, and writing queries. They must be able to work with different platforms, including Microsoft Excel and SQL.
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Skills Required For An Entry Level Data Scientist
1: Which of the following algorithms is most suitable for classification tasks?
To get hired as an entry level data scientist there are many challenges you need to face. There are a lot of skills you need to have to land as an entry level data scientist. Some of the important technical skills you need to have are the following:
Programming skills
A good grasp of programming languages like Python, R, Scala, Java, SQL, etc is important.
Statistical skills
Understanding statistics concepts like data descriptions, linear regressions, etc is vital.
Machine Learning skills
A good knowledge of various supervised and unsupervised algorithms is mandatory.
Probability skills
It is essential to have a probability skill to master machine learning from scratch.
Data Visualization
Must have prior experience in using various tools like Excel, Tableau Power BI, etc.
Business And Domain Knowledge
Understanding the objective and key goals of business and how it influence the work you are doing.
Apart from the technical skills, a data scientist must have some soft skills like the ability to make presentations and communicate effectively.
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Start Learning Now with EMI OptionsTips To Prepare A Successful Career in Data Science Field
- Attain a certificate – Certification validates your knowledge. So enroll in various data science certification programs as well as live projects.
- Acquire real life experience – Without gaining a real life experience no firm will give you high pay. So expand your knowledge and talent by working on various mini projects and also apply for an internship to learn how these things can work in an organization.
- Take part in codefest – Codefest is often conducted by many organizations to hire data scientists. Even though if you couldn’t win participation certification will be awarded for all the participants. It will be beneficial for your career. By taking part in the codefest you will gain a lot of experience
- Broaden your network – You can network through friends, family, alumni groups, or professional associations related to your field. Networking helps you to connect with people who can offer you advice or even help you get hired.
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FAQ’S
Q: Can we get data scientist job without a degree?
Ans: Yes, if you have relevant experience working with different data sets then you can get hired without having a degree in data science or related fields.
Q: What are the qualifications needed to become a data scientist?
Ans: There is no need to have a specific qualification to become a data scientist. You should know programming languages like Python, SQL, etc and awareness of machine learning concepts such as regression analysis and clustering techniques.
Q: What is the mathematical background required for a data scientist ?
Ans: Linear Algebra, Probability and Statistics and Calculus and optimization.
Q: What are the four pillars of data science?
Ans: Domain knowledge, Math and Statistics skills, Computer science, Communication and Visualization.
