The art of data science and analytics is being able to find relevant relationships and connections within large amounts of data sets. It is a sector of the information technology industry that relies on data communication and assessment to find valuable meaning in the information. Where data science focuses on answering specific business questions, data analytics helps those businesses to mine the important data that will find those answers.
Both data science and data analytics are equally important in business operations, and they are both exceptional careers for IT professionals to choose from. Being able to earn a high-paying salary is a dream, and for many, this can be achieved by aiming for one of these 11 highest-paying technology jobs which incorporate data science and analytics.
Database Design and Administration
Starting at the more entry-level positions for this career choice, database design and administration is responsible for monitoring and evaluating large sets of databases all with varying information. Each dataset needs to achieve a specific objective for the business such as answering questions about a customer’s buying habits or online interests. An administrator in this field will need to know how to import and categorize important information in a format that is easy to assess and understand. Each line of information plays a vital role in making important business decisions, and the expected salary for a competent professional is enviable.
An entry-level job in this position will start a person at no less than $80,000 per annum, but this is for less experienced employees. With enough practical experience under their belt, a database administrator can earn closer to $150,000 as a senior employee. The market projections for this field indicate that there will be an annual increase of 10% in the number of qualified professionals needed for the industry. It is a growing sector that is worth looking into and is the ideal place to start for young data scientists and analysts trying to enter the market.
Business intelligence is the process of comparing data between historical and current statistics to indicate how a business operates and should improve. A BI analyst is responsible for evaluating millions of lines of information to assist managers and business leaders to make an informed decision for the company. The main responsibility of this professional entails identifying ways in which business operations can be improved, and where certain operations are resulting in negative outcomes. For example, lowering overhead costs by analyzing departments with redundant responsibilities or where significant shortfalls are experienced are a few ways that BI analysts use data to improve business functions.
A BI analyst can expect to earn about $60,000 starting at an average IT company. More senior analysts can earn two, sometimes three times that and there is no shortage of job vacancies. In 2019 alone, it was reported that the demand for qualified and professional BI analysts rose more than 150% since 2014. This is exciting for those that want a viable career that will be in demand for the next 50 to 100 years.
From running the basic day-to-day functions of an office to analyzing all internal and external processes, operational coordinators are the ones managing everything from behind the scenes. This includes understanding how the business hierarchy functions and how each department correlates and corresponds with each other. There is also a major need for these professionals and operational coordinators can work in any field within any industry. Whether it be manufacturing, healthcare, or finance, operational coordinators are at the backbone of many businesses.
Top earners in this position can make a six-figure salary with enough practical experience and industry knowledge. Whether junior or senior, operational analysts can expect to make about $65,000 and the difference is only really seen for those working in massive technological companies. Smaller businesses still require operational coordinators to run the engine behind the company name, but there is less chance of earning more money than the other careers on this list.
Engineer of Machine Learning
Machine learning is the ability to program machines to learn a variety of complex algorithms to perform complicated tasks. Think about the idea of a self-driving car or any field where a robot needs to carry out the normal tasks of everyday humans. Machine learning is at the forefront of the latest in innovative AI technology. Things like facial recognition, forecasting weather patterns, and body language are just the beginning of what machine learning can offer.
The difficulty of training machines in this manner is that they need to perform without any human intervention or interference. For anyone looking into this career option, they will need a data science master degree such as the one offered by Worcester Polytechnic Institute. This profession could earn the average engineer more than $130,000 with only four years of practical experience. At the moment, machines capable of learning are taking over the basic responsibilities of humans; however, this will change very soon. There will be a radical shift as the technology is advanced and utilized on a grander scale and within more industries.
Anything to do with AI and creating machines that can act in the place of humans is a major space of technology that is being explored. Robotics is focused primarily on hardware for the machine to function, whereas machine learning is fully reliant on programming language and software. Robotics and machine learning work together and there cannot be one without the other.
Japan, for instance, has incorporated robots with sentient features similar to those of a breathing human being. In the healthcare industry, robotics has become an innovative idea that needs to be explored more. Robots are used to administer medicine, change bed linen, and order stock, to free up nurses and doctors for higher priority tasks. A robotics engineer can expect to earn about $100,000 for a starting position in a medium-sized company. It is expected that robotics will be a requirement in schools as well as learning basic coding languages, as the need for qualified students must start from an earlier age. This ensures that by the time those students leave university, they are more experienced and skilled than the current analysts and scientists that only learn these subjects in secondary education.
Architect of Data Warehouses
Data is vitally important for every business. It is the core on which most marketing strategies and operational functions are based. Without the necessary storage systems, data cannot be managed effectively. Information needs to be protected, but it also must be readily available for the necessary people to access. Data architects are among the most desired professions in the IT world. Currently, there is a 16% increase in positions that need to be filled.
This job requires knowledge in data science as well as how computers operate, and experience with various database platforms like SQL Server or Oracle. The envy around this profession is that data architects have full transparency and autonomy to create a database management system that works for them. Each business will function differently, and there is no one correct way to structure a data warehouse. Although not the highest paying job in the tech industry, data architects can still make about $140,000 in different states of the US.
A characteristic of a successful marketing strategy is when it effectively targets the right audiences and yields positive results concerning the budget used. In other words, a marketing strategy must bring in enough business to make it a viable venture. This is where a marketing manager comes in. Not only are they managing a team of designers and social media experts, but marketing managers also need to analyze the information that platforms like Google Analytics and Google Keywords provide. By identifying specific phrases and words that are most associated with a product or service, a marketing manager can tell what strategies work for certain situations.
This profession requires someone that is experienced in digital marketing as well as a person with knowledge about data and computer science. Senior marketing managers with analytic experience can look forward to a minimum of $100,000 every year, but this varies significantly between different businesses and even American states.
A product manager is responsible for determining the requirements of a project and then ensuring that the team finalizes said project in a specific period. Although this position can branch out into multiple others, product managers need good data analytics skills and experience in a whole variety of different programming languages. Essentially, when a large product needs to be delivered, the product manager will monitor everything from the initiation of the project to the final delivery.
Product managers must possess skills in strategic management, knowledge of company policies and procedures, and managing large groups of teams. Managers also need to be well versed in the product being managed and analyze data to identify when business goals and objectives are not being met. With an average salary of a little more than $100,000, product management is a good steppingstone to bigger and better career choices in data analytics and science.
A large part of making big company decisions is being able to understand how various data and real-world issues influence the business. For example, market fluctuations or political changes can have major effects on different companies, and this is where statisticians are useful. Not only do they manage internal data such as a BI analyst would, statisticians look at every bit of data available from all angles.
The main responsibilities are designing processes that work to effectively collect data and working with large amounts of data sets to identify key statistics. Statisticians work mostly in government, physical science, and healthcare, and is a sector of technology that is vital for these industries to function. The base salary for an employee with limited experience is close to $70,000, with more avid statisticians earning more than $110,000. This is another career that will grow more than 30% in the next eight years or so.
The main function of a data modeler is to understand how business trends occur and predict future events based on specific information that is analyzed. A form of enterprise information management, data modelers also work with BI, machine learning, and database engineers. Data modelers are responsible for designing, implementing, and managing data by creating systems that support data analysis. There is a great deal of mathematics involved, so data modelers need to be well versed in algebra, trigonometry, and high-end algorithms.
The basic requirement for this profession is a minimum of a bachelor’s degree in computer and data science and it is only with good experience that a person will earn a decent salary. A skilled professional working as a data modeler can expect a median salary of $150,000 which is substantially more than other jobs in technology.
Financial Wealth Manager
Even within the financial industry, data science and analytics play a major role. A credit bureau, for example, needs to possess important information to make reasonable decisions about wealth management and financial assistance. Finance is the second most common industry in which data scientists are most needed. This profession calls for people that can evaluate the stock market, have experience in financial assets and liabilities, and the brain of a mathematical intellect.
Small financial institutions pay about $80,000 for data analysts and scientists that have recently graduated. The salary bracket varies substantially because it relies on the financial institution in question and its main functions. Insurance companies that work with retirement annuities will pay more for a data analyst because it requires working with a much greater data set, with more complicated mathematical calculations.
These highest-paying jobs within the data science and data analytics field have gained popularity over the last decade since technology and innovation have evolved far beyond comprehension. This field is not easy by any means, and those interested in these careers need to understand that the curriculum is tough, and the industry is always changing. However, the chance to earn a great salary is much more accessible with the right qualifications and experience if this field is of interest.
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