What is data science?
DATA SCIENCE is the field of study that consists of extracting information from vast amounts of data using various scientific methods, algorithms, and processes and there are lots of data science jobs for freshers. However, it helps you discover hidden patterns from the raw data. The term Data Science emerged due to the evolution of mathematical statistics, data analysis, and big data.
it is a multidisciplinary field that allows you to take knowledge from structured or unstructured data. It allows you to translate a business problem into a research project and then translate it into a practical solution.
Data science job roles:
- Data scientist
- Big Data engineer
- Big Data Analytics
- Data architect
- Data administrator
- Business analyst
- Data manager/analytics
A Data Scientist is a professional who manages huge amounts of data to offer convincing business visions using various tools, techniques, methodologies, algorithms, etc. There are no data science jobs for freshers as a data scientist.
R, SAS, Python, SQL, Hive, Matlab, Pig, Spark
Big Data engineer
The role of the data engineer is to work with large amounts of data. He develops, builds, tests, and maintains architectures such as large-scale processing systems and databases. Data science jobs for freshers are easily available as a big data engineer.
SQL, Hive, R, SAS, Matlab, Python, Java, Ruby, C ++ and Perl
Big data analyst:
A data analyst is responsible for extracting large amounts of data. He or she will look for relationships, patterns, trends in the data. Later, he will provide compelling reports and visualization to analyze the data to make the most viable business decisions. Therefore, there are no data science jobs for freshers as a big data analyst.
R, Python, HTML, JS, C, C ++, SQL
The statistician collects, analyzes, understands qualitative and quantitative data using theories and statistical methods. Hence, if you are skilled then there data science jobs for freshers are easy to get.
SQL, R, Python, Tableau, Matlab, Perl, Spark, and Hive
The data administrator must ensure that the database is accessible to all the users concerned. It also ensures that it works properly and is protected against hacking. So, there is no data science job for freshers are available easily.
Ruby on Rails, SQL, Java, C # and Python
This professional needs to improve business processes. In addition, He/she acts as an intermediary between the management team and the IT department. Therefore, without any experience, it is not easy to get data science jobs for freshers.
SQL, Tableau, Power BI and, Python
Data science salaries:
Here are some of the job title of the data science and their salaries for each position:
- Analysis manager: $ 67,000 to $ 126,000
- Big Data engineer: $ 64K – $ 132K
- Associate Data Scientist: $ 58K – $ 101K
- Business Intelligence Analyst: $ 49K – $ 95K
- Big Data analytics: $ 42,000 to $ 83,000
- Senior Data Scientist: $ 95,000 to $ 172,000
- Research Analyst: $ 40K – $ 79K
- Data scientist, IT: $ 61K – $ 135K
- Scientific researcher: $ 48,000 to $ 118,000
- Data architect: $ 77K – $ 153K
- Senior Data Scientist: $ 93,000 to $ 160,000
- Statistician: $ 50K – $ 108K
Why data science as a career?
- Data is the oil for the world today. However, with the right tools, technologies, and algorithms, we can use the data and convert it into a distinct business advantage.
- Data science can help you detect fraud using advanced machine learning algorithms
- It helps you avoid any significant monetary loss
- In addition, it Develops intelligence capacity in machines
- You can perform sentiment analysis to assess customer brand loyalty
- It allows you to make better and faster decisions
- It helps you recommend the right product to the right customer to improve your business.
- Data science job for freshers is easy to get if you are skilled.
Data science process
You need to know this if you are seeking to get a data science job for freshers.
The discovery step is to acquire data from all identified internal and external sources that help you answer the business question.
The data can be:
- Data disseminated from online sources using APIs
- Web server logs
- Data disseminated from online sources using APIs
- Data collected on social networks
- Census data sets
Data can have many inconsistencies such as missing value, empty columns, an incorrect data format that needs to be cleaned up. You must explore, process, and condition the data before modeling. Therefore, the cleaner your data, the better your forecast.
In this step, you need to determine the method and technique for establishing the relationship between the input variables. Hence, the planning of a model is carried out using different statistical formulas and visualization tools. SQL, R, and SAS / access analysis services are some of the tools used for this purpose.
In this step, the process of building the actual model starts. Hence, big data distributes data sets for training and testing. Techniques such as association, classification, and grouping are applied to the training data set. Once prepared, the model is tested against the “testing” dataset.
At this stage, you deliver the final reference model with reports, code, and technical documents. Therefore, the model is deployed in a real-time production environment after extensive testing.
At this stage, the main results are communicated to all stakeholders. This helps you decide whether the project results are a success or a failure based on the inputs from the model.
Applications of Big data :
Google search uses data science technology to find a specific result in a fraction of a second
To create a recommendation system. For example, “suggested friends” on Facebook or suggested videos “on YouTube, everything is done using Data Science.
Image and speech recognition:
Speech recognizes a system like Siri, the Google Assistant, Alexa works on the technique of data science. In addition, Facebook recognizes your friend when you upload a photo with him, with the help of Data Science.
EA Sports, Sony, and Nintendo use data science technology. This improves your gaming experience. In other words, the games are now developed using the machine learning technique. Therefore, it can update automatically when you go to higher levels.
Price comparison online:
Price-runner, Junglee, Shopzilla are working on the Data science mechanism. Here, data is retrieved from the relevant websites using APIs
- Data science is the field of study that involves extracting information from vast amounts of data using various scientific methods, algorithms, and processes.
- However, Statistics, visualization, Deep Learning, and Machine Learning are important concepts in data science.
- The data science process involves discovery, data preparation, model planning, model building, operationalization, and reporting of results.
- The important roles of Data Scientist are: 1) Data Scientist 2) big Data Engineer 3) Data Analyst 4) Statistician 5) Data Architect 6) Data Admin 7) Business Analyst 8) Data / Analytics Manager
- In addition, R, SQL, Python, SAS, are essential tools of data science
- Business Intelligence forecasts are retrospective while for data science, they are looking to the future.
- Important applications of data science are 1) internet research 2) recommendation systems 3) image and speech recognition 4) the gaming world 5) online price comparison.
- Hence, the great variety of information and data is the biggest challenge of data science technology.
- So, if you want data science jobs for freshers then you must have all the skills mentioned above.