If you are looking for the next big occupation Data Science is it. With the emergence of computer languages that interact with specific types of programs and other languages Data science is less an accountant job and more of an investigator role.
Below we list the fields and occupations for Data Scientist, as stated in the latest publishing from the Department of Labor and Statistics.
There are lots of occupations that work with big data in one way or another. The job tasks of these workers are evolving, as are their job titles. Several occupations that might work with big data are described below, along with their relevant job tasks. Managers who work with big data are known as chief data officers or chief information officers. They create the policy for how their organization will use data, as well as supervise the analysts, computer programmers, and other workers. Postsecondary teachers who use big data usually instruct students in statistical analysis and computer science. These teachers may have a lot of expertise and experience working with big data but choose to help new generations of workers develop their skills to enter the workforce. Software developers have an important role in working with big data. They write the computer programs that aggregate, process, analyze, and visualize the data, along with the trends and other useful information that can be found in those data. Software developers generally are not associated with a single industry but create computer programs for use across industries for lots of different data. They may explore alternative sources of data and alter their programs to work with specific kinds.
Business. Increasingly, businesses base their decisions on data. Businesses need workers to collect relevant product data and analyze that data in the context of the industry. Analysts look at purchase data and customer reviews to decide what kinds of improvements or new products they should make to meet their customers’ needs. For example, workers may study transaction data from store loyalty cards to see what types of products customers buy and when they buy them. Big data can also help businesses run more efficiently. Analysts use supply chain data to manage inventories. They also detect errors by studying real time production data.
E-commerce. Purchase-transaction data from commercial websites have long been collected, but now new kinds of big data are generated by commercial websites. Data analysts help a company improve customer service by studying how consumers feel about its products through customer reviews, comments, and suggestions. Many commercial websites use predictive modeling techniques to suggest similar options when users browse products. Analysts also search data to find trends in purchasing or website traffic.
Finance. Account data, credit and debit card transactions, and financial market data are examples of financial big data. Analysts study transaction data to look for fraud and other security breaches. They also monitor investment portfolios and alter them to compensate for increased risk and unexpected price changes.
Government. Governments collect a lot of data about their constituents, but policies and security concerns may keep them from sharing or using that data. However, use of big data can help governments serve their constituents better and improve policy decisions. For example, some governments use data to pre-fill tax or other forms for constituents. Analysts also study constituent satisfaction levels by monitoring social networking sites.
Healthcare. The move toward electronic health records generates even more new uses for patient medical data. Patient data can include video feeds from surgeries and other medical procedures. In addition, remote patient monitoring is becoming increasingly popular, and a way to organize and evaluate data from all these video feeds is now necessary. Analysts use data gathered from drug trials for evidence-based drug therapy and to estimate the cost effectiveness of new drugs. Using social networking, analysts also have created software to track disease outbreaks in real time. Through the Human Genome Project, scientists have mapped electronically the entirety of the structure of human DNA. Analysts work with scientists to devise uses for the vast amounts of data collected by the project. These uses include the development of drugs tailored specifically to an individual’s genetic makeup and the creation of lifesaving medical treatments.
Science. Many different fields of science produce huge datasets. For example, physicists study the properties of particles by colliding them with other particles in high-tech experiments. Data analysts record the location, velocity, and other information about every particle in the experiment. “Particle physics has been dealing with big data since its inception,” says Roser. “We just had to wait for the technology to catch up.” Analysts collect data from the experiment data on site, and then ship them off to another lab to be analyzed. “Big data is underlying all that we do,” says Roser. For example, Fermilab hosts all the data for the Large Hadron Collider. Experiments are done in Europe, and then data are transported to Fermilab for analysts to determine how to house and study them. Other areas of science, such as climatology, chemistry, and biology, also are using these workers to help with the logistics and analysis of large datasets.
Social networking. Data analysts who specialize in social networking study how big data is used after it is generated. Analysts gather huge volumes of comments, pictures, and videos from social networking sites. By sorting these data, the analysts study user preferences that can help create more targeted advertising and better customer services. And as social networking continues to grow, analysts search for new ways to use the rich amounts of data that can be found there. A large portion of the data from social networking websites and online maps and GPS services is personal location data. Even nonhuman objects, such as packages or shipping containers, have location data that are collected and tracked. Analysts use this data to help businesses make better products or advertise more effectively.
Telecommunications. With the proliferation of smart phones, the amount of telecommunications big data has increased rapidly. Smart phones can learn their users’ preferences through their actions and can track user location through GPS data. This allows data analysts who work for telecommunications companies to better tailor their services to their customers’ preferences, based on their phone use. Analysts also study huge amounts of data from phone records to try and minimize dropped calls and other problems.
Other. Other areas where big data increasingly is used include politics, utilities, and smart meters on appliances. Politicians rely on polling data and approval ratings, which were traditionally numerical. Now, however, analysts gather public sentiment data from comments on social networking and other websites. Utility data include power generation and usage information from homes and businesses. Analysts study the data to reduce costs by determining which parts of the system are working at full capacity and where future investments should be made. They can also detect patterns that lead to equipment failure, allowing them to fix outages more quickly. Smart meters are installed on different kinds of equipment, such as cars and electric meters. The meters transmit data about the equipment’s performance. Data analysts examine this data to determine the cause of any malfunctions and help prevent future ones. (For more information about the smart grid, see “Powering the nation: Smart grid careers,” elsewhere in this issue of the Quarterly, at www.bls.gov/ooq/2013/fall/art03. pdf.)
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