In July of 2020, the grid in Delaware was turned over to the robots.
The Delaware Electric Cooperative, a distribution network serving some 84,000 households in Kent and Sussex counties, found their costs burgeoning and member satisfaction waning as traditional methods for predicting and allocating for peak electrical demand began to have difficulty keeping up with a profusion of use and generation patterns. So the small co-op turned to artificial intelligence firm Sonasoft, which delivered NuGene, an AI Bot Engine, to take over electrical peak demand forecasting. After tests in June of 2020, the bot proved so effective that the utility handed off all load control recommendations to AI.
Although it remains to be seen if this development will lead to Judgement Day, it’s part of a broader pattern of data science adoption across the country and around the state. Data scientists with banks like M&T in Wilmington, perform complex analyses of internal data in order to provide summarized reports to company executives, and also write code for databases, maintain current databases, and work to improve data mining systems.
Data scientists also work for companies like Informatic Technologies, Inc. headquartered in Newark, which provides medical imaging, laboratory diagnostics, and medical IT for healthcare provider clients. Data scientists with the company work with clinical research data in order to maintain client databases and identify trends and improvements within the system.
In 2019, executive recruiting firm Burtch Works reported that salaries for data scientists at almost every career level have increased, with the most substantial increase in senior data science manager salaries… ranging up to $250,000 annually for master’s-prepared professionals at the highest levels.
Preparing for a Master’s Degree in Data Science in Delaware
Candidates seeking a master’s degree in data science must meet an intense set of qualifications, including undergraduate education, related employment experience, and knowledge of fundamental concepts. Master’s programs set highly selective admission requirements, and all candidates must typically have a diverse skill set, high scores on graduate entrance exams, and between 5-7 years of previous employment in the data science field.
Undergraduate Degree and Master’s Prerequisite Courses
Applicants to data science master’s programs are required to meet several minimum qualifications in order to be considered for acceptance:
- Bachelor’s degree in a related field (statistics, computer science, engineering, or applied math)
- Minimum of 3.0 GPA during undergraduate studies
Applicants must also complete required prerequisite courses before enrolling in the program. Required courses include:
- Calculus I & II
- Linear algebra
Preparing to Excel in the Quantitative Sections of the GRE/GMAT Exams
In order to be considered for admission, applicants must score in the top 15 percent on the quantitative section of either the GRE or the GMAT exam. Admissions departments also look for applicants with excellent scores in the verbal and writing sections, as all data science professionals are expected to have strong communication skills—discoveries made, but that can’t be explained, are as good as useless in data science.
The Graduate Record Exam (GRE)’s quantitative section will evaluate the candidate’s abilities to perform data analysis and solve basic arithmetic, algebra, and geometry problems. Topics particularly relevant to data scientists include statistics, standard deviation, tables, graphs, and probabilities. To prepare, the candidate can take a free practice exam or view a preparation guide on the quantitative section hosted on the official GRE website.
The General Management Admissions Test (GMAT) also has a quantitative section, which consists of 37 questions on problem solving, data analysis, and data efficiency. To prepare for the GMAT exam, candidates can review test prep materials and take two free practice exams on the official GMAT website, or candidates may choose to take practice exams hosted by The Princeton Review or Veritas Prep.
Gaining Relevant Prior Work and Personal Experience
In order to be accepted into a master’s program, candidates should have several years of experience in data science or a related field. Master’s applications committees look for candidates who have developed and demonstrated some or all of the following skills:
- Strong communication skills
- Programming proficiency in languages such as Java, C++, and Python
- Database administration proficiency
In Delaware, data science professionals can gain the required experience through many different entry-level positions. These can include becoming a data programmer or engineer at local government offices, startups, or nonprofits, or working in almost any industry as a software programmer. Academia is also a good starting point, with statisticians in high demand in data science programs. With a large number of major insurance companies based in Delaware, you might also find actuarial positions as great preparation for an eventual role in data science.
Using an Online Data Science Bootcamp to Acquire Skills for Master’s Applications or a Career Move
Master’s degrees aren’t your only option for getting a job in data science. Demand in the industry is high, and slots in fully-accredited master’s programs are few, so private industry and colleges have come up with another way to prepare for data science work: online and offline bootcamps.
A bootcamp is an intensive short course, lasting only weeks or months, that drills down deep into practical, hands-on instruction in data science topics. You can find bootcamps that exist at every range of the spectrum, from ultra-advanced, highly specialized camps that admit only very experienced master’s and PhD holders, to entry-level programs that will take anyone with ambition and a pulse.
They tend to be organized around a series of set-piece projects that students undertake in a cohort, working as a group to develop analysis and solutions using the same kind of cutting-edge tools and techniques that are deployed in the field today. They do this under the watchful eye of instructors who are themselves highly experienced in real-world applications of that data, and who alter the curriculum as frequently as necessary to keep up with new developments in that fast-paced world.
At first, bootcamps were all developed for in-person learning, but it’s increasingly common to find excellent options online, and a number of these are available in Delaware, including:
- Columbia Engineering Data Analytics Boot Camp
- Georgia Tech Data Science and Analytics Boot Camp
- Penn Data Analysis and Visualization Boot Camp
As programs run in concert with existing universities with excellent data science programs, these all have the added advantage of drawing on deep resources and highly experienced educators. They are also built around a part-time schedule that makes attendance easy for anyone who is still working a regular day job or committed to an existing degree program.
As entry-level programs, they focus on developing basic skills and ground-level techniques in data science, such as:
- SQL language and database applications
- Hadoop and Big Data stores and manipulation
- Fundamentals of statistical science and analysis
- Data visualization through tools like Tableau and D3.js
Like other types of bootcamps, they also have a very solid element of career preparation baked in. That can extend from basic resume development assistance to full-on demo days, where student projects are run in front of hordes of potential employers to demonstrate your skills and capabilities.
While there is a focus on getting direct placements in data science careers at most bootcamps, the nature of the knowledge and skills they teach also serves as excellent preparation for master’s program applications. You can boost your odds of acceptance by preparing yourself with a fast, inexpensive bootcamp program.
Bridge Programs and Massive Open Online Course (MOOC) Options for Master’s Program Applicants Who Need to Fill Gaps in Knowledge
Applicants to data science master’s programs are expected to possess a diverse array of knowledge and skills because master’s course work will build off of prior knowledge and experience with concepts, programming languages, and familiarity working with data sets. If applicants do not possess each of the requirements for admission, most universities offer bridge programs to fill the gaps in education or experience.
Two different types of bridge programs are offered:
- Fundamental bridge programs (includes linear algebra, algorithms, analysis of algorithms, data structures)
- Programming bridge programs, including essential programming languages such as Python, JAVA, and C++
MOOCs are supplementary educational resources designed to help data science master’s students fill gaps in knowledge or learn additional skills, such as programming languages. MOOCs include online problem modules, filmed lectures, and the opportunity to interact with instructors and teaching assistants. A MOOC offers a less directed method for building your skills, but that also comes with the freedom to study when and how you prefer, and to pick classes that more exactly match your needs than a predetermined set of bridge courses.
Earning a Master’s Degree in Data Science in Delaware
Master’s programs in data science are offered in a handful of traditional in-state, on campus programs in Delaware. However, online master’s programs are growing in popularity, offering a broader range of programs and flexibility around a professional schedule. Online options offer fully accredited curriculum and are widely respected by employers nationwide.
Most data science programs require students to complete an immersion experience in their last semester. The immersion program is a hands-on group project that will require online students to visit campus. In addition, students can choose from full time, part time, or accelerated program tracks. Full time programs take 18 months to complete, part-time programs can be completed in 32 months, and accelerated options can be completed in as little as 12 months.
Students may choose from several program titles:
- Master of Information and Data Science (MIDS)
- Master of Science in Data Science (MSDS)
Curriculum Content and Core Coursework
Coursework within master’s programs will vary, but all courses require certain fundamental skills required for data science professionals. Programs will include a curriculum made up of some variation of the following topics:
- Applied regression and time series analysis
- File organization and database management
- Ethics and law for data science
- Network and data security
- Visualization of data
- Data storage and retrieval
- Machine learning and artificial intelligence
Key Competencies and Objectives
Data science master’s programs seek to prepare students for the challenges of working in the field. Students are expected to become competent in the following areas:
- Communication and visualization of results
- Research design
- Database queries and data cleansing
- Statistical sampling techniques
- Data collection and analysis
- Data mining and machine learning
Career Opportunities for Data Scientists in Delaware with Advanced Degrees
In Delaware, data scientists are employed by a broad range of companies to help derive insights from company data as well as to maintain and improve internal data systems. As recruiting firm Dice noted in their 2020 Tech Job Report, Data Engineer was the fastest growing job role in 2019, with demand up 50 percent year over year. That represents a broad-based hiring demand across Delaware’s industries, which means plenty of opportunities for anyone with the right skillset.
The following job listings are shown as illustrative examples only and are not meant to represent job offers or provide any assurance of employment.
Data Scientist in Newark, DE
- MS or Ph.D. in data science, chemical engineering, computer science, or mathematics
- Experience with data mining and machine learning
- Conducting hands-on research and development in partnership with the data science team
- Using data mining to monitor business operations, plant production and processes
- Evaluating and developing data mining algorithms using advanced regression techniques
Risk Data Scientist in Wilmington, DE
- Master’s or Ph.D. in data science or related discipline
- 5 years experience using Python or similar software
- 5 years experience in financial sector
- 5 years experience building predictive models
- Developing credit risk and scorecard models for business lending
- Performing data mining, analysis, and optimization of decisions
- Exploring data solutions to optimize models and decision making process
Director of Data Science at Anthem in Wilmington, DE
- Master’s in data science or a related field
- 7 years experience in predictive analytics
- Advanced expertise with Python, R, SAS, SAS Enterprise Miner or equivalent
- 3 years experience leading advanced modeling teams
- Leading a team of data scientists engaged in development of machine learning algorithms to solve business problems
- Providing guidance to the team on working with varying datasets
- Piping and processing massive data streams in distributed computing environments