There are a range of skills required to analyze the data collected from various sources and derive an actionable insight out of it. Data Science is one vast field that helps companies in collecting and interpreting this data, in order to develop strategies which can help in growing the revenue of the company. The field of Data Science requires expertise in Statistics, Scientific Methods, Data Analysis, and Artificial Intelligence to extract value from the raw data.
Also including designing and implementing multiple data system models, the field aims to make the data available to each and every person in the organization. These large scale expectations put various hats on the head of a Data Scientist. As a result, there is also a lucrative Data Science Salary which these professionals earn.
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The Data Science Certification in Denver is in huge demand currently, and the hiring in the industry has increased by 46% compared to 2019 level [Source: India Today]. As various companies have come up with new job openings for data science experts, there has been observed a conflict of work domain between these roles. Here, in this article, we look at the top job roles in the data science industry and the key responsibilities these professionals hold. Have a look.
Data Science Roles
Data science projects are typically overseen by 3 types of departments.
- Business: They address the problem and develop a strategy for analysis. The data science team works based on the strategy formulated by the business team. They could have roles like a Business Intelligence Developer.
- IT: IT members support data science operations with infrastructure and architecture. They monitor operations to ensure that the data science teams operate securely and efficiently. Common job roles in this domain include Data Architecture and Data Engineer.
- Data Science: They manage the data science team and analyse the collected data to find patterns and trends. Candidates here work on roles like Data Scientist, Data Analyst, etc.
Some of the important data science roles have been explained below. Please note that all the salary figures have been picked from payscale.com.
Data Scientist
Data Scientists are involved in all aspects of the project. They are required for building the business strategy, analyzing data, and finally visualizing & presenting them. They are usually team leaders, who manage the people with specialized skill sets. They overlook the projects and guide and supervise from the beginning till the end.
Average Salary: ₹8,54,985
Responsibilities of a Data Scientist
- Management: They manage various planned and continuous data analytics projects. They also manage and lead the skilled people working in the particular project.
- Analytics: They plan, implement and assess high-level statistical models for various problems including classification, projections, clustering, patterns, sampling, simulation, etc.
- Strategy: Data Scientists develop innovative strategies to understand the consumer trends and solve business related issues.
- Collaboration: They collaborate with other data scientists and stakeholders to communicate about the obstacles and findings to drive business performance and decision making.
Data Analyst
Data analysts are responsible for various tasks like transforming, manipulating and visualizing data. They usually prepare the data for communication by creating reports that clearly show the
trends and insights gathered from the analysis.
Average Salary: ₹4,47,224
Responsibilities of a Data Analyst
- Data Mining: They do data mining from primary and secondary resources, then organize them in a format that is easily understandable for humans and machines.
- Data Analysis: They analyze data using various statistical methods and identify trends and patterns in the complex data sets.
- Data Visualization: Data Analysts present the data in the forms of charts, tables and graphs to make it easier to understand.
- Report Preparation: These professionals also prepare reports that effectively communicate the trends, patterns, and predictions extracted from the data.
- Collaboration: Analysts work along with engineers, programmers, and organizational leaders to identify various new opportunities.
Data Engineer
Data engineers build systems that collect, manage, and convert raw data into structured and organized information that can be used to interpret trends. They usually build algorithms for easy access of data to everyone in the organization.
Average Salary: ₹8,53,317
Responsibilities of a Data Engineer
- Analyze and Organize Raw Data: Data Engineers build machine learning models of clustering and classification to scan, label, and categorize the unstructured data. This gives rise to structured data which can be easily stored and organized.
- Building Data Systems and Pipelines: They build pipelines to capture data from various platforms and store them in a warehouse, which are then cleaned, analyzed and finally sent to the destination systems.
- Building Algorithms and Prototypes: The pipeline is an automated set of actions that is usually powered by an algorithm. Data engineers build these algorithms so that the extraction and analysis of data can be done automatically.
- Evaluating Business Needs and Objectives: Data Engineers try to understand the business needs and objectives, so that they can build the algorithm and pipeline based on that.
Data Architect
A Data Architect understands the needs of the business and offers a blueprint for building a framework of easily accessible, secure data, aligned with business strategy. These professionals express strategic requirements and also provide high-level integrated designs to fulfill those requirements.
Average Salary: ₹20,41,159
Responsibilities of Data Architect
- Developing and Implementing Data Strategy: They develop and implement an overall organizational data strategy that is in line with business processes. The strategies could include database development standards, data model designs, data analytics systems, and management of data warehouses.
- Implementing the Overall Proposed Solution: They handle everything from managing end-to-end architecture, selecting platforms, designing technical architecture, to finally testing and implementing the solution.
- Ensuring Proper Technical Functionality: They make sure that all the functions are being conducted properly, like data accessibility, accuracy, and security.
- Conducting Regular Audits: Data Architects conduct regular audits to check the performance of the data management system, refine whenever required, and report any breaches or loopholes to the stakeholders.
Candidates get to earn a really good Data Science Salary in India, as the career holds vital importance in an organization. As this field continues getting bigger, it is recommended to keep a check on new job opportunities and the key skills which are being demanded by organizations. If required, do go for a certification course in Data Science to sharpen your skills. This is one field which can give a boost to your career and you won’t regret joining it. You can visit here to know about the forexrenkocharts. On the other hand, you can also get more essential info on taylorsource. Here is the best news portal sttmag where you can get the latest news around the world views360
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