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What is Data Science and Why It is Important?
Data Science definition in simple words:

“Data Science is a multi-disciplinary domain which is made of three different fields of studies, i.e., Computer Science, Mathematics & Statistics, and Domain Expertise”.

In other words, Data Science is the study of raw information/data in bulk, to understand what it represents and how it can be effectively turned into valuable and actionable insights, which help business owners to make various strategic decisions.

Here below find what a Data Scientist has to say:

“I am fascinated about Data Science as it gives the pleasure of unraveling mysteries. Makes you feel a scientist, a detective, domain expert, deal complex problem with facts and no gas!”– Sandhaya Kumari (Data Scientist).

Quite often than not, you open Facebook, and, after every few scrolls you observe a Sponsored Ads column of various products. These are of those products that either you might have been checking out online or something that matches your taste or preference based on your previous social media engagement. But how did Facebook know that?

Well! Since the inception of Big Data and Data Science Technologies, analyzing and predicting visitors’ taste and preferences is no more a mystery. Facebook’s targeted advertisement is so powerful that it can reach you based on Location, Demographics, Behavior, Interests, and Connections too.

CNBC reports that, Facebook made $40 billion in advertising revenue last year, second only to Google.

Data Science has numerous benefits in terms of Business and Career. In the modern market landscape, ‘customers are kings’, and to meet their expectations, companies have to go an extra mile and look beyond just offering the minimal requirement.

That is when Data Science plays a vital role, and a company-wide deployment of Data Science techniques is only going to let the organizations stand out from the rivals. Let’s dive deep into the reasons why businesses need Data Science.

Benefits of Data Science for Businesses
‘Data Science’ is a buzzword that has been the talk of the tech-town over this decade. But what makes Data Science so compelling that more and more companies are inclining towards this emerging technology?

McDonald’s spends heavily on Data Analytics and Data Science to compete with Burger King considering their usual rivalry with the latter always remaining second to the former. However, Burger King also leveraged Data Science and Data Analytics to first enhance the customer experience through various digital mediums which caused a huge increase in the footfall.

Data Science is taking healthcare industry to a whole new level by offering complicated services in lesser cost, whether it is Medical Image Analysis, Genetics & Genomics, Drug Discovery, Virtual Assistance, and many more areas.

Walmart uses Data Science technologies to manage the order/shipment preparations, transportation, routing, managing inventory levels, etc., all of which are seamlessly handled with the help of heuristics offered by Machine Learning Algorithms.

Read this exciting blog on How AI helps fight against Coronavirus!

How Data Science Helps?
Following are some the prominent ways Data Science is helping businesses unlock methods of achieving success:

Predicting Customer Preferences: Data Science comes with predictive analytics techniques that allow companies to track customers’ preferences and helps offer them customized services. This not only traces new potential customers; it also helps them retain the existing ones at a lesser cost.
Competitive Edge: While every other company is racing to reach the top and acquire larger market share, Data Science has emerged as the superhero helping them channelize their resources in a way that can help them develop a competitive edge over the rivals.
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How To Build A Data Science Career In 2021

For this week’s data science career interview, we got in touch with Dr Suman Sanyal, Associate Professor of Computer Science and Engineering at NIIT University. In this interview, Dr Sanyal shares his insights on how universities can contribute to this highly promising sector and what aspirants can do to build a successful data science career.

With industry-linkage, technology and research-driven seamless education, NIIT University has been recognised for addressing the growing demand for data science experts worldwide with its industry-ready courses. The university has recently introduced B.Tech in Data Science course, which aims to deploy data sets models to solve real-world problems. The programme provides industry-academic synergy for the students to establish careers in data science, artificial intelligence and machine learning.

“Students with skills that are aligned to new-age technology will be of huge value. The industry today wants young, ambitious students who have the know-how on how to get things done,” Sanyal said.

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50 Data Science Jobs That Opened Just Last Week

Our latest survey report suggests that as the overall Data Science and Analytics market evolves to adapt to the constantly changing economic and business environments, data scientists and AI practitioners should be aware of the skills and tools that the broader community is working on. A good grip in these skills will further help data science enthusiasts to get the best jobs that various industries in their data science functions are offering.

In this article, we list down 50 latest job openings in data science that opened just last week.

(The jobs are sorted according to the years of experience r

1| Data Scientist at IBM

**Location: **Bangalore

Skills Required: Real-time anomaly detection solutions, NLP, text analytics, log analysis, cloud migration, AI planning, etc.

Apply here.

2| Associate Data Scientist at PayPal

**Location: **Chennai

Skills Required: Data mining experience in Python, R, H2O and/or SAS, cross-functional, highly complex data science projects, SQL or SQL-like tools, among others.

Apply here.

3| Data Scientist at Citrix

Location: Bangalore

Skills Required: Data modelling, database architecture, database design, database programming such as SQL, Python, etc., forecasting algorithms, cloud platforms, designing and developing ETL and ELT processes, etc.

Apply here.

4| Data Scientist at PayPal

**Location: **Bangalore

Skills Required: SQL and querying relational databases, statistical programming language (SAS, R, Python), data visualisation tool (Tableau, Qlikview), project management, etc.

Apply here.

5| Data Science at Accenture

**Location: **Bibinagar, Telangana

Skills Required: Data science frameworks Jupyter notebook, AWS Sagemaker, querying databases and using statistical computer languages: R, Python, SLQ, statistical and data mining techniques, distributed data/computing tools such as Map/Reduce, Flume, Drill, Hadoop, Hive, Spark, Gurobi, MySQL, among others.

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5 Indian Companies Recruiting Data Scientists In Large Numbers

According to a recent study on analytics and data science jobs, the number of vacancies for data science-related jobs in India has increased by 53 per cent, since India eased the lockdown restrictions. Moreover, India’s share of open data science jobs in the world has seen a steep rise from 7.2 per cent in January to 9.8 per cent in August.

Here is a list of 5 such companies, in no particular order, in India that are currently recruiting Data Scientists in bulk.

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Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

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'Commoditization Is The Biggest Problem In Data Science Education'

The buzz around data science has sent many youngsters and professionals on an upskill/reskilling spree. Prof. Raghunathan Rengasamy, the acting head of Robert Bosch Centre for Data Science and AI, IIT Madras, believes data science knowledge will soon become a necessity.

IIT Madras has been one of India’s prestigious universities offering numerous courses in data science, machine learning, and artificial intelligence in partnership with many edtech startups. For this week’s data science career interview, Analytics India Magazine spoke to Prof. Rengasamy to understand his views on the data science education market.

With more than 15 years of experience, Prof. Rengasamy is currently heading RBCDSAI-IIT Madras and teaching at the department of chemical engineering. He has co-authored a series of review articles on condition monitoring and fault detection and diagnosis. He has also been the recipient of the Young Engineer Award for the year 2000 by the Indian National Academy of Engineering (INAE) for outstanding engineers under the age of 32.

Of late, Rengaswamy has been working on engineering applications of artificial intelligence and computational microfluidics. His research work has also led to the formation of a startup, SysEng LLC, in the US, funded through an NSF STTR grant.

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