There are few career choices as lucrative as those based on numbers. While many skills are becoming increasingly antiquated, numbers-based professions are becoming ever more crucial.
Furthermore, there is a diverse range of applications that this field is involved in. These range from the strictly scientific realm to business, sociology, farming, and even sports.
Numerical processes are used to optimize manufacturing, fine-tune marketing approaches, gain insight into social issues, and quantify the impacts of climate change.
In our modern, data-driven world, a career in numbers is an excellent choice for both young prospective college students, and current working professionals wishing to shake up their occupations.
Broadly speaking, careers that are numbers-based are generally considered “tech.” However, it is difficult to define exactly what constitutes the tech industry in a single article. As such, some of the more prominent numbers-based tech careers will be focused on below.
How to Prepare for a Numbers-based Career
The first aspect of preparation for a career in numbers is to build a solid knowledge base. Proficiency in certain fundamental topics is crucial including:
- An affinity for mathematics.
- A solid grasp of statistics.
- Interest in programming/coding is also essential as languages such as Python and R will be some of the tools needed to analyze data.
- Understanding the skills related to the subfield of the tech career you are interested in such as familiarizing yourself with manufacturing processes, big data, or sociological experiments.
Tech Degree
To work in tech, higher education is generally required. Most employers will want to see at least a bachelor’s degree, but many prefer a master’s.
There are scores of different universities offering tech majors. Each of these will have a unique program with varied options of focus. Like many STEM majors, the first years of schooling will focus on fundamental principles.
Building blocks such as mathematics, statistics, computer programming, and perhaps engineering-related courses as well.
One example of an in-demand, and numbers-based tech career to pursue is data science. Here is an example first-year course list for UC Berkley’s data science bachelor’s program.
- Data C8: Broadly accessible introductory data science course.
- Data C100: Principles and techniques of data science.
- Data C102: Develops the probabilistic foundations of decision-making in data science.
- Data C104: Human context and ethics of data
- Data C140: Probability for data science.
These courses would likely be taken during the first semester of freshman year and offer students the opportunity to better understand what they are getting into. The freshman and sophomore years would then include the following types of courses.
- Calculus I and II: Integration and derivations in mathematics.
- Linear algebra: The analysis of matrices (crucial in computations)
- Programming structures: How programming languages and data are structured.
- Statistics: In-depth study of the applications of statistics.
- Programming in statistics: An introduction to and elaboration on the programming languages frequently used in statistical analysis. For example, Python, R, and MATLAB.
Once the student has progressed to their third and fourth years, their coursework will become more focused and specialized. It is at this point that the student will have more leeway in what they choose to study.
As mentioned before, tech is a very broad field and encompasses many areas of study. These career track focuses could be one of the following.
- Big Data: As the name implies, this is the study of large data sets as they relate to populations. More sociological, big data is focused on the behaviors of people as a group. For example, the analysis of polling data to predict elections or the effectiveness of targeted advertising.
- Machine Learning: Perhaps one of the more exciting subfields, this branch of AI focuses on software applications that can make predictions and adapt in real-time without needing to be actively programmed to do so.
- Statistics: Although an older field in and of itself, modern statistics requires tech in one form or another. There are broad applications of statistics ranging from actuarial (insurance) to financial.
- Data Analysis: Although this encompasses many things, data analysis is particularly important for the manufacturing industry. With proper data analysis, manufacturing processes can be optimized to reduce waste.
- Computer Science: Data science and computer science are very closely intertwined. One cannot exist without the other. Computer science is the study of computation at a fundamental level.
- Mechatronics engineering: Modern mechanical devices rely heavily on electronic interfaces. For example, newer cars are dependent on commands received from onboard computers to function properly. Therefore, there is an increasing demand for people who understand the complex relationship between computation, electronics, and mechanical devices.
- Web Design: A contrast to the other names mentioned on this list, web design is a more artistic career path for those with robust creativity. Making websites appealing to visitors is at the core of this subfield and will require knowledge of design, artistry, digital editing, and even content writing.
Once completing a bachelor’s degree, many students studying tech will go on to pursue a master’s degree. A master’s degree is usually less structured than a bachelor’s and different universities will offer different paths to completing one.
The three most common paths are course-based, research-based, and project-based:
- A course-based master’s degree, as the name implies, would consist of strictly coursework building on the knowledge gained in your undergrad.
- A research-based master’s degree would consist of blended coursework and research that takes up several semesters. A typical scenario would be assisting professors in your program with conducting research projects. This would involve experimentation, writing proposals, and presenting findings.
- A project-based program would involve collaborating with a large corporation and assisting them in either developing a new product or resolving an issue they currently have. These types of master’s are often the most popular as they provide opportunities to make connections in the corporate world that could eventually lead to employment. Most universities in today’s day and age also offer online/hybrid learning options for those currently employed.
Internships
Acting as a bridge between the academic and corporate worlds, internships are an excellent way to test the waters of your new career.
An internship is a part-time or full-time position at a company lasting anywhere from several weeks to around a year. The job duties of an intern are typically centered around doing lower-level easier tasks related to their career while getting exposure to the day-to-day duties of working in tech.
This internship may be either paid or unpaid depending on the employer. If an internship goes well, it could lead to employment right upon completing a bachelor’s or master’s program.
Training Programs
Although the bulk of training for tech careers is obtained from undergraduate degrees, graduate degrees, and internships, certain essential skill sets may be reinforced via training programs. The most obvious example of this is computer coding.
Several organizations and universities offer training programs often referred to as coding bootcamps. These programs typically span several weeks and act as an intensive and immersive experience for data scientists.
A few examples are:
- Python: This language is often the go-to for engineers and scientists alike due to its intuitive nature and the fact that it is open-source. It also uses plain English syntax which is ideal for beginners.
- R: Known as “R”, is more specialized than Python and is used primarily for statistical analysis that can handle large, complex regression models.
- SQL: Pronounced as “sequel”, this language is used for querying structured data. Large databases can be managed by programs run by SQL.
The following are a few examples of programming language one might learn at a coding bootcamp:
- Python: This language is often the go-to for engineers and scientists alike due to its intuitive nature and the fact that it is open-source. It also uses plain English syntax which is ideal for beginners.
- R: Simply referred to as “R”, this programming language is more specialized than Python and is used primarily for statistical analysis. Large, complicated regression models can be created using R.
- SQL: Pronounced as “sequel”, this language is used for querying structured data. Large databases can be managed by programs run by SQL.
These are just a few examples of programming languages someone in tech may use. Although less common, other bootcamp-type classes might cover software packages that will likely be used in school and on the job such as MATLAB or Excel. Certain training programs may even involve crash courses in Adobe or other digital editing software packages aimed at web designers.
Special Scholarships
There are usually two types of scholarships (also known as fellowships) available for prospective students.
The first type of scholarship is known as “need base”. To qualify for this type of assistance, an individual will need to demonstrate a financial need and/or belong to an underrepresented community.
The other type of scholarship is based on merit. Prior strong academic performance, professional references, and essay submission are typically required.
Various organizations are offering both types of scholarships with varying degrees of financial assistance. For example:
Intel/AFCEA Diversity Scholarship
This needs-based scholarship caters to female, African American, Hispanic, Native American, and active/former military members who earned above a 3.0 GPA in high school. Financial assistance is $2,500 for undergraduates and $3,000 for graduate students.
Herbold Fellowship
Offered through the University of Washington, the Herbold scholarship is aimed at students whose future career focuses exclusively on data science. However, other majors in STEM are invited to apply.
Although underrepresented students are preferred, the fellowship is primarily merit-based and for graduate-level studies. On top of prior academic achievement, a GPA of 3.5 must be maintained during studies. However, it offers a generous $10,000 per school year in aid.
SMART Scholarship Program
Offering $25,000 – $38,000 in tuition assistance, the Science, Mathematics, and Research Transformation Scholarship-for-Service Program (SMART) is run by the U.S. Department of Defense.
It is a merit-based scholarship that comes with an obligation to work for the D.O.D. once a degree is completed. This would also act as a great stepping stone into government and defense-based employment.
Numbers-based Career Paths
Earning a bachelor’s and master’s degree is just the beginning of a tech career in numbers. Once out of school, graduates are faced with the daunting task of choosing a career path.
Due to its extremely broad nature, tech grads have a wide range of sub-fields they can situate themselves in. As previously mentioned, careers in tech are extremely lucrative now and often come with generous salaries and benefits packages.
For example, According to the Bureau of Labor and Statistics, the median annual pay for data science grads is $103,500 and a 10-year growth rate of 35 percent (much faster than average).
Although public sector jobs exist, the tech industry is where most will be employed in the private sector. Although not a comprehensive list, here are just a few examples of what recent tech grads can do for work.
Data Scientist
A data scientist both analyzes and interprets data. This is particularly useful in a business setting where decisions must be made regarding revenues and costs. Data analysts present their findings to business executives in ways that they can understand so that informed decisions can be made. For example, a responsibility may be analyzing market trends and revenue forecasts and communicating the findings to colleagues.
Median Annual Salary: $136,620
Data Architect
A data architect acts as the mastermind behind the design and management of a corporation’s data. Such a position is most prevalent in software and tech companies such as Google or Apple. A data architecture position is typically not entry-level and will require prior work experience.
Median Annual Salary: $112,120
Data Manager
Data management is more centered around business practices than the technical aspect of this career. They ensure that proper data flow is accomplished and perfect data sharing processes. Additional duties may include assessing data quality, management of metadata, and even management of entire departments of a corporation.
Median Annual Salary: $108,359
Machine Learning Engineer
Perhaps one of the most exciting and lucrative careers on the list, a machine learning engineer creates systems for artificial intelligence (AI). This job requires a comprehensive understanding of software engineering, computer modeling, and statistics. AI technology can learn from experience and improve on itself which has significant implications for both the manufacturing and service industry.
Median Annual Salary: $161,531
Marketing Analyst
It is no mystery that corporations are increasingly using big data to create more effective marketing strategies. A marketing analyst will use their skills in programming and statistics to help develop these strategies and make their products more appealing to prospective consumers.
This includes not only analyzing data but also creating marketing plans and campaigns. For those interested in the more sociological aspect of data science, such a career path may be favorable.
Median Annual Salary: $68,230
Mechatronics Engineer
A rapidly growing subfield of tech, mechatronics engineering is an excellent career choice for those who are both computer savvy and enjoy hands-on work. Mechatronics is a field of engineering that innovates new ways to blend software, electronics, and mechanical components.
This is particularly important in the fields of robotics, automation, and transportation. However, mechatronics is also very important to sustainability. For example, hybrid and electric vehicles are reliant on a symbiotic relationship between software, onboard computers, electric motors, and batteries.
Median Annual Salary: $104,000
Statistician
The career of a statistician is more specialized than others on the list. These individuals focus solely on the statistical side of their industry and use their skills to create models or analyze prior events. This profession is particularly important in the business, medical, insurance, and educational realms.
Median Annual Salary: $99,960
Web Designer
For those with a more artistic bent, becoming a web designer may be an excellent career choice. A large portion of tech is focused on the coding aspect of web development, but who makes the final product presentable and aesthetically pleasing? Working as a web designer requires creativity and taste. As an employee, one will spend hours perfecting the designs of websites to make them more appealing and intuitive to users.
Median Annual Salary: $55,513
Conclusion
For driven and analytically minded individuals, the world of tech provides an excellent direction for their careers.
This dynamic field is characterized by rapid innovation, high earning potential, and a constant influx of exciting challenges.
With a promising future, high earning potential, and stimulating challenges, it’s a great career choice for both new and experienced professionals.