The increasingly growing data landscape and need to process voluminous data sets are making data science a most-demanded job across diverse industry verticals. As the COVID-19 crisis has shifted companies’ operations towards remote work, interactions across digital interfaces are growing rapidly along with raising the reliance on data and machines. This is the reason organizations are actively looking for data engineers and data scientists to process, churn and assess data to deliver competence.
Data scientists have the potential to operate between the business and IT ecosystem and drive industries by evaluating complex datasets to untangle insights. The demand of data science professionals has been highly reckoned by industry experts, making it a shout after career opportunity for those who want to play in the modern data world.
The wave of big data is gaining rapid momentum and winning this massive wave require to have a better understanding and knowledge to dig deep through the data to derive and deliver insights. This is where data science has a role to play that involves data analysis, data mining, predictive analytics, business intelligence, deep learning, and much more.
Pursuing a career in this inter-disciplinary field of study, the first and foremost thing candidates should consider is where will new data science skills take your career? If you are ready to land your career in data science, you must acquire skills like data analysis, data wrangling, machine learning, data visualization, statistics, programming skills, etc. Besides, candidates must have communication and problem-solving skills that will help them become a data science expert.
Explore Job titles in Data Science.
• Data Analyst
• Data Engineer
• AI Product Manager
• Database Administrator
• Business Analyst
• Data and Analytics Manager
With millions of job openings across the world in Big Data, a career in data science roles has become the hottest job of the 21st century. Getting data science certifications are a great way to gain an edge in this evolving field. They will enable candidates to develop skills and help recruiters and hiring managers to hire the best talent.
With acquiring the right qualifications, an aspirant will enjoy a bright career outlook as a data scientist. Let’s have a look at top data science certifications that will assist you to stand out in the most-demanded career in IT.
• Dell EMC Data Science Track
• Google Data and Machine Learning
• IBM Data Science Professional Certificate
• Microsoft MCSE: Data Management and Analytics
• Google Certified Professional Data Engineer
• Microsoft Certified Azure Data Scientist Associate
• Open Certified Data Scientist (Open CDS)
• SAS Certified Advanced Analytics Professional
• SAS Certified Big Data Professional
• SAS Certified Data Scientist
These certifications will promise you to increase an edge and provide the ability to create skills that are apt for a candidate’s ideal industry.
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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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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
Skills Required: Real-time anomaly detection solutions, NLP, text analytics, log analysis, cloud migration, AI planning, etc.
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.
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.
Skills Required: SQL and querying relational databases, statistical programming language (SAS, R, Python), data visualisation tool (Tableau, Qlikview), project management, etc.
**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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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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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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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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