Data science jobs include an all-encompassing field of work that deals with scientific methods of collecting data and the different processes involved in extracting information from the data that is collected. Data science uses statistics and the analysis of those statistics to create solutions to a variety of everyday problems. Data science professionals utilize skills from an array of academic specialties including math, science, statistics and technology. Below are some of the top jobs in the industry of data science and details on what each of these sub-specialties does within the field.
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Data scientists are analytical experts who fuse curiosity to explore trending problems with the ability to use data to create solutions to these complex issues. Part mathematician and part computer scientist, data scientists are on the lookout for current trends in the business and technical world and use statistical analysis to come up with innovative ways to solve these problems.
Decades ago, data scientists weren’t in demand. Times have changed in the last 20 or 30 years, and we now live in the electronic age. Operating businesses and having a successful life requires a lot more technological ingenuity. Data scientists can be employed by major retailers to assist in crunching the numbers and understanding how to apply statistics to ensure a successful bottom line.
Data science jobs can be found in the financial industry. Data scientists use modeling to predict consumer trends and to mitigate impacts of changing trends. The financial industry also uses predictive modeling and machine learning to monitor markets to detect fraud. Data scientists develop models that can detect an uptick in identity theft or credit card fraud as well as insider trading. Investment bankers also use data scientists to develop algorithms to automate trading.
Professional service industries use data scientists to identify data sources, develop databases and provide analysis. Law firms may use data to analyze case outcomes. Manufacturers may use data to optimize production. Advertising firms may use data scientists to identify and an analyze data to effectively target consumers.
The technology industry is a huge employer of data scientists. Social media platforms depend on data-driven algorithms to target marketing and predict behavior. The e-commerce industry uses data science to predict consumer shopping behavior geographically and stock warehouses accordingly.
Data scientists typically possess a bachelor’s degree in data science or other related field. Coursework includes software engineering, data structures, machine learning, statistical analysis, risk analysis, data mining and math.
No matter what their specialty is, every business continually collects data. This data must be analyzed, studied, and applied using techniques that improve the functionality of the company and enhance its profitability. This is where the data analyst comes in. Data analysts translate this statistical information into a language that everyone can understand and make use of.
All businesses have costs of operation, and all are constantly trying to strike a balance between affordable costs and superior customer service. Data analysis can be used to help these businesses make better decisions regarding their operating costs. This, in turn, allows them to save money while still providing the same great service that their customers have come to expect. Data analysis might be used to help source more affordable materials, reduce transportation costs involved in operating a business, or find real-world solutions to problems that are costing the company a lot of money.
Data analysis is a multi-step process. The first step is identifying the question you’d like answered. It is important to have a specific goal in mind in order to know what you are looking for and what data needs to be collected to solve a specific problem. Next you need to collect the necessary raw data either from internal company databases or secondary sources such as government records. This data needs to be cleaned before it can be analyzed. This involves making sure duplicates are removed and making sure the data is in a consistent format to be more easily analyzed. Finally, the data needs to be analyzed. This step is where data analysts shine. Data analysts use various analysis techniques to try an identify patterns in the data. This analysis is then interpreted and applied to the specific problem’s solution.
There are several types of data analysis. Descriptive analysis simply tells the story of what happened. For example, descriptive analysis may show you a trend of increased patient admissions to a hospital. Diagnostic analysis may help answer why that is happening, for example if the influx of patients is due to one particular disease. Predictive analysis makes predictions about future behavior based on past behavior. If hospitals see more flu cases in the winter, predictive analysis may allow hospitals to predict which months may see an increase in patients admitted. Prescriptive analysis uses all the previous analysis to inform a solution to the predicted trends. In the hospital example, prescriptive analysis may recommend that hospitals increase staffing during the winter months.
Every day, more and more business is being conducted online. It seems that new websites offering innovative products or services appear daily. All these websites require extensive data analysis to function with a successful profit margin in order to make a solid name for themselves in a seemingly endless sea of competitors. Data architects use their analytical skills to gather and interpret this information needed to help online business owners succeed in their endeavors.
Data architects are responsible for creating and overseeing a company’s data management framework. They are responsible for translating a company’s business needs into technology needs for an organization’s data. They are responsible for creating data standards for an organization including modeling, client data, vendors, security, employees and materials. They set reference standards for improvements to data systems. Data architects also identify and design data flow systems within an organization. Typically, data architects start out as data scientists or data engineers and work their way up to data architect after years of experience with data management, data design and data storage.
Data engineers build on what data architects bring to the table. Data engineers develop, maintain, evaluate and test out the solutions that data architects come up with to assist companies to become more successful. Data engineers utilize a precise knowledge and understanding of software engineering and combine this with experience in coding and testing patterns in order to create usable solutions to common problems faced by organizations everywhere.
Data engineers are responsible for building systems to consolidate data from different data sources within an organization. They are responsible for cleansing data and preparing data for analysis. They create systems to make data accessible and are responsible for data system optimization. In a large corporation, they write software to collect data from various sources and put it into a central destination or database. They make data optimized and accessible for data scientists and data analysts to use.
Data engineers typically posses a bachelor’s degree in mathematics, computer science, or engineering. They should be proficient in many programming languages such as C#, Java, Python, Ruby, Scala, and SQL. They should also have a good understanding of relational databases, data lakes and business integration platforms.
Although statisticians are often overlooked regarding their importance, they provide the very backbone for the field of data science jobs overall. Statisticians are experts in the gathering, preparation and analysis of statistics. Numbers are involved in the planning, upkeep, advancement and modification of all types of business models everywhere. Statisticians are the key players who collect this information, analyze it thoroughly and turn it into something that a business can use to enhance its productivity, save money and improve customer service.
Statisticians are vital to any organization that relies heavily on data. They apply their expertise in mathematics and statistical analysis to aide in addressing specific problems by providing targeted data manipulation and analysis as well as identifying trends in data that may not otherwise be obvious. They use their critical thinking skills to analyze data within the mindset of the specific problems facing their organization to use data effectively. Besides excellent statistical skills, statisticians use their expertise to communicate data findings and solutions to those that may not be experts in the field. Most statisticians hold a master’s degree in statistics or math with coursework in computer science and any specialized field of study such as biology or economics.
In this information and technology age, gone are the days when critical data was stored in filing cabinets on paper. Nearly all vital information that a company relies upon to improve its bottom line is stored in computer databases. Database administrators are responsible for the important task of backing up this information in case something goes wrong with the original software or the way in which it is stored. Database administrators ensure that this data is easily accessible to those who need it but safe from unauthorized access as well. They essentially serve as the gatekeepers and protectors of the vital information that helps keep businesses operating smoothly and successfully.
Database administrators are responsible for making sure that the data in the database is easily accessible in the format needed for use by data analysts and others in the company. They are also responsible for maintaining the database and ensuring that the database continues to operate efficiently and error free by continual testing. They also make any modifications to the database necessary with changes in technology and the needs of the company and ensure seamless transfer of data from old databases to new. Database administrators regulate security and dynamically monitor permissions and access. They keep data safe by making sure there is a foolproof back up system in place in case of disaster.
Business analysts are generally a little less technologically savvy, but they make up for this by offering a deep knowledge of the different processes involved in running a successful business. They are masters at connecting this insight to real world strategies that enable businesses to become more successful. Consider them the go-between party that merges the technical side with the business side of things, bringing the two together to offer solution-oriented strategies targeted at successful business operations.
Business analyst help bring efficient and effective change to organizations. They help bridge the gap between business and technology by creating models for realistic and cost-effective goals for business solutions and realistic expectations for currently available technology. They engage with business leaders to help them understand the data driven solutions that will work best for the organization. Business analysts must use communication skills as well as business and technology skills to help an organization efficiently use data to achieve goals.
Data and Analytics Manager
Data and analytics managers are the cheerleaders of the team. They are responsible for ensuring that the right goals and priorities are set for all parties involved. Data and analytics managers require the strong social skills needed to lead a team of independent individuals, as well as the technical know-how to gather and analyze data and conduct thorough research.
Data and analytic managers bring together teams of data professionals to oversee data driven solutions for an organization. They are responsible for all data going into and out of an organization. Data and analytic managers keep track of company data and search out any anomalies. They are also responsible for rectifying any data issues within the company. They must be able to communicate with data teams from a variety of areas as well as company leadership and report data trends and issues. They may also make recommendations about upgrades or changes to an organization’s data hardware or software.
In the world of business, there is room for all manner of professionals in data science jobs that offer the experience and expertise needed to gather and analyze data and use it to come up with real solutions to common, everyday problems that business owners face. Running a successful business and overcoming obstacles is a complex series of events that requires professional input from a variety of specialists.
Data science jobs offer a wide variety of career choices that are exciting and solution-oriented for those who are technically inclined. The world today runs on data and data science jobs are increasingly in demand. We hope this basic overview of the many career possibilities available in the world of data science jobs has answered some of the questions you have had on this topic.