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a-guide-to-make-career-in-data-science

A Guide to Make Career in Data Science

Take admission in B. Tech- Data Science in collaboration with IBM at Mangalayatan University to make rewarding career as a Data Scientist.

Today, Data Scientist is one of the most popular career options. According to the report by the World Economic Forum in 2020, Data Scientist will be one of the most popular careers with immense growth. The advancement in technology and the generation of huge amounts of data have led to the great demand for Data Scientists across the globe in sectors like information technology, telecom, manufacturing, finance, and insurance, retail, etc. Today data is one of the most valuable assets for organizations; collecting, analyzing data, and extracting useful information from it enables organizations to determine and thus influence the trend in the particular industry. Data Science encloses state-of-the-art technologies like Artificial Intelligence (AI), Internet of Things (IoT), and Deep Learning.

What is Data Science?

Data Science is a multidisciplinary domain in which mathematics, statistics, and computer science are applied to extract insights from structured and unstructured data. Three core components of data science are organizing, packaging, and delivering data. A Data Scientist uses his/her mathematics, statistics, and programming acumen to clean and organize the data. The analysis of a data scientist combined with industrial knowledge helps to uncover hidden solutions to business challenges.

Skills Require to Make a Career in Data Science:

Proficiency in Mathematics and Statistics:

Differential calculus, partial differential equations, integral calculus (AUC-ROC curves), linear algebra, statistics, and probability theory.

Proficiency in Computer Science:

  • Aspirants should have excellent knowledge of programming languages like Python, Java, Perl, C++, and Scala.
  • Familiarity with database programming languages like SQL and NoSQL.
  • Strong command over business intelligence tools like Tableau.
  • Big data tools, machine learning techniques, algorithms will all be considered as additional skills.

Job Profiles in Data Science:

Data Scientist:

A Data Scientist works in diverse domains. He/she defines the problem statement, project objectives in line with the business goals. Using mathematical and technical acumen, a data scientist identifies patterns and trends and makes prediction based on data. A Data Scientist has a strong command over subjects like artificial intelligence, machine learning, statistics, and data engineering.

Business Analyst:

A Business Analyst works with the business and management team, identifies business needs, and solves problems by designing technical solutions. Generally, Business Analysts help organizations to grow by their technical and management acumen. They play a pivotal role in framing company’s marketing strategy and financial planning.

Data Engineer:

A Data Engineer develops and maintains scalable data pipelines and builds APIs to support the data repositories. The data models have become diverse in nature and knowledge in data formats, big data technologies to populate data models has become a necessity.

Enterprise Data Architect:

An Enterprise Data Architect works strategically for organizations, his/her primary job responsibilities are ensuring the quality of the data, accessibility, and security. Identifying the layers of technology, an Enterprise Data Architect builds and maintains the database of organizations.

Future Prospects of Data Science:

E-Commerce:

There is a great for data science professionals in the E-Commerce sector. These professionals play an instrumental role in the growth of E-commerce companies. Effective and impeccable data analysis helps e-commerce organizations to predict the purchases, profits, losses, and even manipulate customers into buying things by tracking their behavior. Below are primary job responsibilities of data science professionals in E-Commerce companies are:

  • Identifying Consumers
  • Recommending Products
  • Analyzing Reviews

Manufacturing:

There are immense possibilities for Data Science in the manufacturing sector. Today, there are plenty of loopholes in these sectors like inefficiency in business operations, low productivity, flaws in the supply chain, and loss in the business. Below are few areas where data science can bring change in the manufacturing sector.

  • Improve performance, better quality, and detecting flaws.
  • Effective and efficient supply chain management.
  • Predictive and conditional maintenance.
  • Global market pricing.
  • Automation and the design of new facilities.

Banking and Finance:

Banking and Finance is one of those sectors where data science can put a profound impact. From data security, transaction details, fraud management to maintaining customer’s personal information; data science can redefine the working methodology of banking sectors. Data Science applications in the banking and finance sector are:

  • Fraud detection
  • Credit Risk Modelling
  • Customer Lifetime

Health Care:

From offering better care to providing actionable insights from previous patient data, Data Science has immense possibilities to revolutionize the healthcare sector. Data Science applications in the health care sector are:

  • Medical History Analysis
  • Drug Discovery
  • Virtual Analysis

Top Recruiters:

Amazon, LinkedIn, IBM, Walmart Labs, Busigence Technologies, Fractal Analytics, Sigmoid, Flipkart, Mate Labs, Couture, etc.

Job Profiles and Salaries (Annual Package in INR)

  • Software Engineer: 2,51,000 – 10,00,000
  • Data Analyst: 1,97,000 - 9,12,000
  • Data Scientist: 3,37,000 - 20,00,000
  • Business Analyst, IT: 2,86,000 – 10,00,000

Why Choose B. Tech - Data Science (In Collaboration with IBM) at Mangalayatan University:

  • B. Tech- Data Science association with IBM is an ambitious and farsighted programme by Mangalayatan University aims to prepare skillful data science professionals.
  • The University lays stress on experimental learning. Here students implement their theoretical knowledge in practical data analytic setting after gaining a strong foundation in the fundamentals of Computer Science.
  • With applied and constructive teaching methodology students understand and use the theory of Computer Science.
  • Industry best practices and practical projects are used to provide world experience of Data Science & Analytics to our campus.
  • Some important skill sets taught in this specialization are Predictive Analytics, Data Analysis & Management, Data Visualization, Business Intelligence, SAS Programming, Programming tools like R, Python, etc.
  • Excellent opportunity to understand intricacies of Data Science by experts of IBM and renowned academicians of the University.
  • Excellent placement and internship opportunities in renowned organizations.

For B. Tech- Data Science admission, students can directly call or WhatsApp at +91-9359-555-555 or Apply Online at https://www.mangalayatan.in/online-application-form/

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