Different Job Roles After A Data Science Course

Different Job Roles After A Data Science Course

Today word data science is the most popular technology. It is a very demanding and very desirable technology. Increment in electronic devices increases the data or information and analyzing those data is a very difficult task. Using data science, we can analyze huge amounts of data easily and get valuable information from bulk of data.

A data science career is rewarding and lucrative, but the way to start a career in data science is not that simple. You do not need any degree to become a data scientist you need good skills and experience in this field to become great in data science. This article will help you understand the career pathways and required skills and how to start a bright career in data science.

To start a successful career in data science, you just need to have hard skill sets like analysis, machine learning, statistics, neural networks, etc. and you must be a problem solver, critical thinker, and a good storyteller to excel in data science. There are thousands of online training institutes which help you to achieve your goal. “Uncodemy” provides a data science certification course in Delhi which helps you to understand the concept behind data science and also, they will help you to get the right way to choose data science as your career.

Now let’s see what kind of job role you can get by choosing data science as your career. Some of them are written below:

Job Roles in Data Science

•      Data Analyst
•      Data Engineers
•      Database Administrator
•      Machine Learning Engineer
•      Data Scientist
•      Data Architect
•      Statistician
•      Business Analyst
•      Data and Analytics Manager

1. Data Analyst

Data analysts have a big job in any organization and they are also very desirable these days as well because the increment in data in every organization gives very difficult for the business to analyze all the systems and find a better way for development. Data analysts are responsible for a variety of tasks including, visualization, munging, and processing of massive amounts of data. They also have to perform queries on the databases from time to time. One of the most important skills is optimization. This is because they have to create and modify algorithms that can be used to cull information from some of the biggest databases without corrupting the data.

Few Important Roles and Responsibilities of a Data Analyst include:

• Extracting data from primary and secondary sources using automated tools
• Developing and maintaining databases
• Performing data analysis and making reports with recommendations
• Analyzing data and forecasting trends that impact the organization/project
• Work with another team to collect data.

2. Data Engineers

Data engineer has a huge responsibility in any organization they build and test scalable Big Data ecosystems for businesses so that the data scientists can run their algorithms on data systems that are stable and highly optimized. They update the existing systems with newer or upgraded versions of the current technologies to improve the efficiency of the databases. They synchronize the system and data scientists’ interactions.

 Roles and Responsibilities of a Data Engineer:

• Structure Design and maintenance of data management systems
• Data collection/acquisition and management
• Conducting primary and secondary research
• Finding hidden patterns and forecasting trends using data
• Collaborating with other teams to perceive organizational goals
• write reports and update stakeholders based on analytics

3. Database Administrator

The job profile of a database administrator is pretty much self-explanatory- they are responsible for the proper functioning of all the databases of an enterprise and grant or revoke its services to the employees of the company depending on their requirements. They are also responsible for database backups and recoveries.

  Roles and Responsibilities of a Database Administrator:

• use database software to store and manage data
• design databases and develop them also.
• Implementing security measures for database
• Preparing reports, documentation, and operating manuals
• Working closely with programmers, project managers, and other team members

4. Machine Learning Engineer

Machine learning is popular data science. Teaching machines so, they can take its decision by their experience. Machine learning is a domain of artificial intelligence.

Machine learning comes in the AI it is widely used in present-time devices like phones, laptops, websites, web servers, applications, etc. Apart from having in-depth knowledge of some of the most powerful technologies such as SQL, REST APIs, etc. machine learning engineers are also expected to perform A/B testing, build data pipelines, and implement common ML such as classification, clustering, etc.

Roles and Responsibilities of a Machine Learning Engineer:

• Designing and developing Machine Learning systems
• Researching Machine Learning Algorithms
• Testing Machine Learning systems
• Developing apps/products basis client requirements
• Extending existing Machine Learning frameworks and libraries

5. Data Scientist

A data scientist has the responsibility to analyze the whole system and give the best solution for the development of business. They help the organization to take better decisions for their company using the whole data of the business and analyzing those data.

For instance, they are expected to perform predictive analysis and run a fine-toothed comb through “unstructured/disorganized” data to offer actionable insights. They can also do this by identifying trends and patterns that can help the companies in making better decisions.

Roles and Responsibilities of a Data Scientist:

• Identifying data collection sources for business needs
• Processing, cleansing, and integrating data
• Automation data collection and management process
• Using Data Science techniques/tools to improve processes
• Analyzing large amounts of data to forecast trends and provide reports with recommendations
• Collaborating with business, engineering, and product teams

6. Data Architect

You can say that they are the architecture of the database they create the blueprint of the whole database system so, that the databases can be easily integrated, centralized, and protected with the best security measures. In their blueprint, they define all the criteria and the structure of the database. They also ensure that the data engineers have the best tools and systems to work with.

Roles and Responsibilities of a Data Architect:

• Identifying data collection sources in line with data strategy
• Collaborating with cross-functional teams and stakeholders for smooth functioning of database systems
• Planning and managing end-to-end data architecture
• Maintaining database systems/architecture considering efficiency and security
• Regular auditing of data management system performance and making changes to improve systems accordingly.

7. Statistician

A statistician understands statistical theories and data organization. Not only do they extract and offer valuable insights from the data clusters, but they also help create new methodologies for the engineers to apply.

 Roles and Responsibilities of a Statistician:

• Collecting, analyzing, and interpreting data
• Analyzing data, assessing results, and predicting trends/relationships using statistical methodologies/tools
• Designing data collection processes
• Communicating findings to stakeholders
• Advising/consulting on organizational and business strategy basis dat
• Coordinating with cross-functional teams

8. Business Analyst

They have a good understanding of how data-oriented technologies work and how to handle large volumes of data, they also separate the high-value data from the low-value data. In other words, they identify how Big Data can be linked to actionable business insights for business growth.

Roles and Responsibilities of a Business Analyst:

• Understanding the business of the organization
• Working on improving existing business processes
• Analysing, designing, and implementing new technology and systems
• Budgeting and forecasting
• Pricing analysis

9. Data and Analytics Manager

A data and analytics manager oversees the data science operations and assigns the duties to their team according to skills and expertise. Their strengths should include technologies like SAS, R, SQL, etc. 

Getting a certificate by Data Analytics online training course in Delhi will help you to find a better career.

Roles and Responsibilities of a Data and Analytics Manager:

• Developing data analysis strategies
• Researching and implementing analytics solutions
• Leading and managing a team of data analysts
• Overseeing all data analytics operations to ensure quality
• Building systems and processes to transform raw data into actionable business insights
• Staying up to date on industry news and trends