Of all the industries in the world that are associated with big data, almost no one thinks to put the jewelry business at the top of the pile. But for Cranston-based jeweler Alex and Ani, it was the ticket to a $1 billion market valuation in 2018, skyrocketing from a mere $2.2 million in revenues reported in 2009.
Long before other retailers started combing website clickstream data and social media behaviors for crucial marketing information, Alex and Ani was using what it could gather from apps, its own website, and third-party data including geolocation information, to build highly detailed customer profiles and engage in precision targeting that other companies simply couldn’t compete with. It was one of the earliest examples of a focused and successful big data campaign outside the core technology industry, but it will hardly be the last.
The need for data scientists is exploding as private companies in a number of industries rely more heavily on the compilation and analysis of large datasets to help them conduct business. Public agencies also increasingly rely on compiling and analyzing data to help them formulate public policy. With everyone finding new needs and applications all the time, jobs in the industry are exploding. Job search engine DICE found that two out of the top three fastest expanding job categories in tech for 2020 were data science and engineering, and the Bureau of Labor Statistics forecasts that 11.5 million new jobs will be created in the field by 2026.
Both private companies and public agencies in Rhode Island have high-powered data analysis centers located here. For instance, Anchorage-based Axiom Data Science has one of its two satellite offices in Providence. The company provides data management services to large-scale research projects and specializes in physical/ecological data and climate modeling. Its clients have ranged from Shell to the USGS and NASA.
The state of Rhode Island invests heavily in data mining so less sophisticated users can access its data to formulate public policy. The Rhode Island Data Sharing Project provides the Rhode Island Data Hub with datasets from multiple state, federal, and local sources. Uses for the data range from health and education to economics and justice.
With all kinds of new opportunities coming online in Rhode Island, earning a master’s degree is a smart step to take to excel in this lucrative field.
Preparing for a Master’s Degree in Data Science in Rhode Island
The competitive nature of data science graduate programs typically requires applicants to meet high standards that include a relevant undergraduate education, high scores on entrance exams, and relevant work experience. It’s not easy to get into these programs, and you need to begin preparations early to boost your chances.
Undergraduate Degree and Master’s Prerequisite Courses
Graduate schools that offer data science programs start off by looking for students who have the appropriate educational background for this field. This kind of foundational preparation typically involves:
- Bachelor’s degree in a quantitative field such as computer science, statistics, applied math, or engineering
- Coursework that includes key disciplines such as calculus I and II, linear algebra, statistics, quantitative methods, and programming languages
- Minimum GPA of 3.0
Relevant Personal and Work Experience for Admissions
Just getting the right education isn’t enough, though. Practical, hands-on experience is also part of the package. Typically, graduate schools seek applicants with highly relevant professional experience:
- At least five years of technical work experience, particularly employment that demonstrates quantitative skills
- Personal experience related to mathematics, database administration, statistics, programming, or analysis
- Strong communication skills
Examples of qualifying local experience in Rhode Island that may satisfy these requirements include:
- Data warehouse development with CVS
- Software engineering with Fidelity Investments
- Data engineering with Brown University’s Data Science Project
- Software engineering with VoltServer
Just holding down the job title and putting in your 8 hours doesn’t cut it, however. It is important to perform high quality work to solicit laudatory letters of recommendation, which are often also required to be admitted into a master’s program in data science.
Preparing for the GRE/GMAT Exams
Scoring in at least the 85th percentile of the GRE and/or GMAT is one way to demonstrate core competency in key data science skills. Preparation for these exams is essential unless you qualify for a waiver, and students who have taken the exams strongly recommend working through sample math problems from the practice tests available.
The quantitative section of the GRE exam evaluates the candidate’s skills in algebra, geometry, arithmetic, and data analysis. Candidates interested in a career in data science should pay particular attention to probabilities, statistics, and standard deviation. Sample questions and free practice exams can be found at the official GRE website.
The General Management Admissions Test (GMAT) evaluates a candidate’s quantitative, verbal, and writing abilities. Admissions departments expect high scores in all of these areas, but particularly in the 37 questions that assess data efficiency and problem solving. Candidates can take GMAT practice exams through Veritas Prep and The Princeton Review®.
Online Data Science Bootcamps to Prepare For Your Master’s Program Application or Direct Career Entry
As luck would have it, not everyone happens to come to data science with the right bachelor’s degree and work experience to blow the socks off admissions committees. But don’t fret; there is a fast, relatively inexpensive path to get the kind of education and practical experience you will need: a data science bootcamp.
If you’re guessing from the name that it’s going to require some hard work, well, yes, that’s part of the deal. But in a period of only weeks or months you can make up for years of choices that were otherwise taking you down the wrong path for a data science career. That hard work will involve studies in cutting-edge technologies like:
- Big Data analysis and Hadoop data stores
- SQL Server, Postgresql, and MySQL database design and administration
- Quantitative analysis
- Programming languages like R and Python
- Dedicated analytics libraries like Numpy and pandas
- HTML and CSS for data visualization
All of this is offered through realistic projects that you engage with in concert with other students in your cohort, breaking down problems and applying concepts in the same way that you would do in the real world, and often using the same live data. It’s all taught by instructors who are coming straight from the front lines and have all the latest tips and tricks for success in the industry.
With these kind of entry-level programs, you can get a quick start in data science tools and techniques, while holding down a regular job or attending courses in other areas… each are offered on a part-time, evening and weekend basis. At the same time, they bring to bear all the significant resources and expertise that comes with being connected to a major university department, giving you experienced instructors and highly-developed career services to help you shape that CV into exactly what an employer or master’s admissions committee is going to want to see.
Closing Gaps in Functional Knowledge Through MOOCs and Bridge Courses
For some students, a bootcamps is overkill, though. You may have taken most of the right courses, gotten most of the right experience, but still find yourself with one or two gaps in your knowledge that need to be filled in. There are other, faster ways to get up to speed if that’s the case.
Massive Open Online Courses (MOOCs) are one way to acquire skills that a candidate may not have obtained in his or her education or experience. These types of courses are educational programs hosted online, often through major universities, and designed to be taken asynchronously, as convenient, in a wide variety of specialty areas. You proceed at your own pace and select the best match for your personal aspirations.
Bridge courses are just regular undergraduate courses that are often available to students that have been accepted into a graduate program, but who may need to fill some gaps in knowledge before beginning master’s-level coursework. The two types of bridge programs typically available are:
- Programming bridge programs – training in such essential programming languages as Java, C++, and Python
- Fundamental bridge programs – courses in algorithms and their analysis, data structures, and linear algebra
Earning a Master’s Degree in Data Science in Rhode Island
Rhode Island has some big name universities with well-develop data science master’s programs available, but online programs have become another solid option for state residents looking to complete relevant graduate studies without relocating. Such programs offer greater flexibility to working professionals and are offered in accelerated, full-time, and part-time formats. Accelerated options can be completed in as little as 12 months. Full-time options can be completed in 18 months, while part-time programs can be completed in 32 months.
While the initial coursework is entirely online, most programs include an immersion experience in the final semester. An immersion experience involves having the student take intensive classes on campus and provides an opportunity to network with peers and professors.
Degree programs available online include:
- Master of Science in Data Science (MSDS)
- Master of Information and Data Science (MSDS)
- Data Mining and Application Graduate Certificate
- Graduate Certificate in Data Science
Core Curriculum Content
The coursework will vary in different master’s programs, but the core courses will cover essential skills that data science positions require. All programs will include these topics:
- Data mining
- Data research design and applications
- Network and data security
- Experimental statistics
- Statistical sampling
- Applied regression and time series analysis
- Experiments and casual inference
- File organization and database management
- Information visualization
- Machine learning and artificial intelligence
- Ethics and law for data science
Key Competencies and Objectives
Master’s programs in data science equip their graduates with a wide array of proficiencies in diverse areas that employers are interested in. Those essential competencies include:
- Data mining and machine learning
- Data cleansing
- Statistical sampling
- Research design
- Ethics, privacy, and relevant law
Career Opportunities for Data Scientists in Rhode Island with Advanced Degrees
Rhode Island offers no shortage of opportunities for employment as a highly trained data scientist in the private and public sectors. The dominant industries of healthcare, financial services, education, advanced manufacturing, and defense all rely heavily on data manipulation and analysis for their success.
In addition to its numerous start-up companies, Rhode Island is home to the financial powerhouse Fidelity Investments, which has its Customer Knowledge & Strategic Insights division in Smithfield. Part of this division includes the company’s Advanced Analytics & Data Science group, which employs data scientists with a passion for machine learning and predictive modeling.
Upon graduating with a master’s degree, students will have the opportunity to apply their academic training to real-world problems and solutions in Rhode Island’s public or private sectors. The information on these jobs is presented solely to illustrate the variety of data science positions available in Rhode Island and should not be construed as current job offers or an assurance of employment.
Data Scientist II with Metlife in Warwick – This position performs and manages data mining, business analytics projects, predictive modeling, and basic to complex research. The position requires a strong working knowledge of advanced data mining tools. While applicants can meet the requirements with a bachelor’s degree in a technical field and at least 2-4+ years of related experience, the work requirements for candidates with a master’s degree are only 0-2+ years of related experience.
Research Engineer Data Scientist with Airbus in Newport – Airbus was seeking a data scientist for its Computation Intelligence and Services team. Technical requirements include knowledge of machine learning, pattern recognition, statistical analysis, and an object oriented language such as C/C++. Candidates must be willing to learn and develop skills around new technologies such as Big Data & Analytics, Python, and Java. Educational requirements include at least a master’s degree in Artificial Intelligence, Applied Mathematics, or Computer Science.
Senior Manager of Data Science & Innovation with CVS Health in Woonsocket – This individual must have a strong knowledge of big data systems such as Hadoop, Aster, Tableau, and SAS and will direct a team of one to two data scientists. The end goal of this position is to use big data analytics tools to enhance customer loyalty and growth. Required qualifications include 5+ years of experience in customer behavior analytics, marketing research, database marketing, or customer analysis and insight development. In addition, the candidate must have 3+ years of analytic leadership experience/team management. CVS prefers candidates with a master’s, MBA, or PhD.
Data Scientist for Utilidata in Providence – Candidates must be proficient in the art of stochastic time series analysis and the modeling, estimation, and ID of stochastic systems to address cyber security challenges in the electric grid. Requirements include advanced expertise in Matlab and 7+ years of experience in modern control theory, state space representation, system identification, subspace ID, blind ID and source separation. In addition, the individual must be able to develop models and algorithms and have experience in the analysis of complex datasets. A master’s is a requirement for this job with relevant coursework in statistics preferred.