Data Scientist Definition
Data scientist define as a professional who is responsible for collecting, analyzing, and interpreting large amounts of data is known as Data Scientist. Also, the role of data-scientist is an outcome of some traditional technical roles, involving the roles of mathematicians, scientists, statisticians, and computer scientists. In addition, After becoming a data scientist, door will open for best career in today’s world. To become a great Data scientist you need to read this.
This work requires the use of developed analytical technologies, machine learning, and predictive modeling. Also, data scientists need massive amounts of data to create hypotheses, make inferences, and analyze market trends and customers. Also, primary responsibilities include the collection and analysis of data, and the use of various types of analysis and reporting tools to discover patterns, trends, and relationships in data sets.
Opportunities for Data Scientist
Data scientists are not only responsible for business analysis. But they are also involves in the creation of data products and software platforms, as well as the machine learning algorithms and developing visualizations
Some of the most significant titles of Data Scientist are:
Data Scientist
Data scientists explore different data models to measure the impact on the organization. The main function of a data scientist is to be able to explain the importance of data in a simpler way that others can understand. They must have statistical knowledge of different programming languages necessary to solve complex problems.
Data Analyst
Analyzing data to identify market trends in the role of a data analyst. It helps to provide a clear picture of the company’s position in the market. Once the business has set the desired goal, the data analyst will give the data sets to complete the required goal. The role of a data analyst can vary depending on the needs of the business. For example, a marketing department may need its services over a period to understand consumer behavior and their responses to different marketing strategies.
Business Intelligence Analyst
A business intelligence analyst helps to analyze the collected data to maximize the efficiency of the business, thereby generating more profits.
Their role is a technical than analytical, requiring more knowledge of current machinery. They should act as a bridge between the business and IT, helping them to improve. A business intelligence analyst must know a particular industry and industry trends.
Marketing Analyst
The role of the marketing analyst is to assist the company’s marketing department. They analyze and recommend, which products should be mass-produced and which products should be canceled. Tracking consumer satisfaction reports can help improve existing products and services. Also, they decide which products to sell and their price.
Skills for becoming a Data scientist
Technical Skills
They can be learned through diplomas, courses, specializations, and certificates.
Statistical Analysis
Statistical analysis is used to generate statistical data from stored data. The results can then be analyzed to bring meaningful information and conclusions about the analyzed entity.
Programming Skills
You will use the programming language to organize, clean, and understand data. Therefore, you have to master how to use it to perform these basic tasks effectively. Skilled in languages like R, Python, Perl, Java, C/ C++, and SQL. Python and R are the most important programming languages used for data science coding.
Data Mining and processing
It is the method of collecting information from a huge database. With the help of certain methods, knowledge is discovered and then used to make business decisions.
Ideal for handling unstructured data is not organized in a predefined way. Data scientists must be aware that most of the data they use is unstructured, so they must develop the skills to manage and collect valuable information.
An understanding of Business
The data scientists working with the company are working hard to generate growth and profit for the company. Also, a deep understanding of how companies operate, what is important to them, etc.
As every business generates huge numbers of data every day, the data scientist’s task becomes enormous. Knowing how the business works, how businesses are successful, will help them to effectively improve their technical skills so that businesses can experience real economic growth.
Data Intuition
Data intuition is the result of the massive processing of data. When there is no logical and superficial aspect, it is the ability to detect patterns and capabilities in the data
Communication Skills
Although it is not necessary to be Excellent in English or any other language, you must know how to express ideas effectively to others. Data science is a complicated and professional field, and most people don’t understand its details. Also, it is useless to use vocabulary. What a data scientist must do is clarify highly complicated concepts into simple terms and easy-to-understand examples.
Minimum Qualification for becoming a Data Scientist
You must have a college or university degree. It must be a formal 3 or 4-year bachelor’s degree. It must be one of the following: science, engineering, business administration, business, and mathematics.
Alternatively, you can achieve a master’s degree in mathematics or statistics. You must get at least 50% or equivalent in whatever subject you graduate. Students must achieve a degree from a reputable college or university.
For this kind of data science certification training, colleges or universities have very high standards. Also, the university or college must have a high reputation.
Role and Responsibilities of Data Scientists
Data scientists work closely with business stakeholders to understand their goals and determine. Also how data can be usable to achieve those goals.
The design data modeling processes, develop algorithms and predictive models to extract the data in the business needs and enable analyze the data and share insights with peers. Each task is different, however, the statistics collection and analysis method generally follows the following path:
Start the process by asking the right questions.
- Acquisition of data
- Processing and cleansing of data
- Data integration and storage
- Preliminary research and exploratory data analysis
- Select one or more potential models and algorithms.
- Apply data science methods such as machine learning, statistical modeling, and artificial intelligence.
- Measure and improve results.
- Show the final result to stakeholders.
- Make adjustments based on comments
- Repeat this process to solve new problems
Salary of Data Scientists in India
Chennai and Bangalore are the highest salaries cities in India for data scientists. However, because Bangalore is the business capital of India. Also it offers the largest number of job opportunities for startups. The salary of data scientists in Bangalore may be higher than in other cities because it is consider as the center of India’s tech industry.
The average salary of a junior data scientist in India is 511,468. Also, the average annual salary of an early career data scientist with 1 to 4 years of experience is 773,442 Employees with 5 to 9 years of experience will be able to earn 12 to 14 Lakhs Indian rupees. According to the salary table, the average salary of an intermediate data scientist is 1,367,306
Data Scientist Training Institutes in India
- Jigsaw Academy
- AnalytixLabs
- IMS Preschool
- Edvancer V.
- Simplilearn
- Nikhil Analytics
- Ivy Professional School
- Imarticus Learning
- Edureka
- Inventateq
How to prepare for an interview
- Read the job description for the specific position you’re interviewing for.
- Review your resume before each step of the interview process
- Follow Glass Door for past interview questions
- Ask employers about the interview structure.
- Conduct mock interviews.
- Practice the skills you’ll be tested on.
Benefits of Data Scientists
Demand
Data science is in high demand. Potential job applicants have many opportunities. This is the fastest-growing job on Linkedin, and an estimated 11.5 million jobs will be created by 2026. Also, this makes data science a field with a high employment rate.
Amount of Positions
There are very few people who are skilled enough to become a complete Data Scientist. This makes data science less saturated than other IT disciplines. So, data science is a very rich field and offers many opportunities. The field of data science is in high demand but few data scientists are available.
Well-paid career
Data science is one of the highest-paying jobs. According to Glassdoor, data scientists receive an average of $ 116,100 per year. Also, this makes data science very profitable employment.
Data science is very flexible
There are many applications of data science. It is widely used in the healthcare, banking, consulting services, and e-commerce industries. Also, data science is a very flexible field. Therefore, you will get the chance to work in many different fields.
Data science improves data
Businesses need trained data scientists to process and analyze their data. They not only examine the data but also develop its quality. Therefore, data science is dedicates to enriching the data and improving it for the business.
Data scientists are prestigious
Data scientists enable companies to make more informed business decisions. Companies trust data scientists and use their expertise to deliver better results for customers. Also, this gives data scientists an important place in the company.