Data Scientist Careers: Applied Orientation for the Beginners

Authors

  • Mahesh Babu Pasupuleti Data Analyst, Department of IT, TekSystems Inc, 200 S College St Suite 1200, Charlotte, NC 28202, USA

DOI:

https://doi.org/10.18034/gdeb.v5i2.617

Keywords:

Data Scientist, Data Scientist Career, Big Data, Data Scientist Skills

Abstract

A data scientist's job is making sense of complex, unstructured data that comes from a variety of sources, including smart devices, social media feeds, and emails, and that doesn't cleanly fit into a database structure. According to the findings of this study, Data Scientists require programming, mathematics, and database abilities, all of which may be learned by self-study or through formal education. Companies looking to hire a Data Science team must be aware of the wide range of tasks that Data Scientists may fill, as well as the need for soft skills such as storytelling and connection building in addition to technical abilities and knowledge. The interpretation emphasizes that high school students interested in pursuing a career in Data Science should learn programming, mathematics, databases, and, most importantly, exercise their newfound knowledge. The study's findings centered on data scientists as analytical specialists who employ their expertise in both technology and social science to discover patterns and manage data. The solutions to business difficulties are discovered via the use of industry expertise, contextual awareness, and skepticism of current assumptions.

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References

Adusumalli, H. P. (2016a). Digitization in Production: A Timely Opportunity. Engineering International, 4(2), 73-78. https://doi.org/10.18034/ei.v4i2.595

Adusumalli, H. P. (2016b). How Big Data is Driving Digital Transformation?. ABC Journal of Advanced Research, 5(2), 131-138. https://doi.org/10.18034/abcjar.v5i2.616

Archenaa, J., and Anita, E. M. (2015). A survey of big data analytics in healthcare and government. Procedia Computer Science, 50, 408-413. DOI: https://doi.org/10.1016/j.procs.2015.04.021

Pasupuleti, M. B. (2015a). Data Science: The Sexiest Job in this Century. International Journal of Reciprocal Symmetry and Physical Sciences, 2, 8–11. Retrieved from https://upright.pub/index.php/ijrsps/article/view/56

Pasupuleti, M. B. (2015b). Problems from the Past, Problems from the Future, and Data Science Solutions. ABC Journal of Advanced Research, 4(2), 153-160. https://doi.org/10.18034/abcjar.v4i2.614

Pasupuleti, M. B. (2015c). Stimulating Statistics in the Epoch of Data-Driven Innovations and Data Science. Asian Journal of Applied Science and Engineering, 4, 251–254. Retrieved from https://upright.pub/index.php/ajase/article/view/55

Srivathsan, M., and Arjun, K. Y. (2015). Health monitoring system by prognotive computing using big data analytics. Procedia Computer Science, 50, 602-609. DOI: https://doi.org/10.1016/j.procs.2015.04.092

Tomar, D., and Agarwal, S. (2013). A survey on data mining approaches for healthcare. International Journal of Bio-Science and Bio-Technology, 5(5), 241-266. DOI: https://doi.org/10.14257/ijbsbt.2013.5.5.25

Young, S. D. (2015). A big data approach to HIV epidemiology and prevention. Preventive medicine, 70, 17-18. DOI: https://doi.org/10.1016/j.ypmed.2014.11.002

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Published

2016-12-31

How to Cite

Pasupuleti, M. B. (2016). Data Scientist Careers: Applied Orientation for the Beginners. Global Disclosure of Economics and Business, 5(2), 125-132. https://doi.org/10.18034/gdeb.v5i2.617

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