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. In fact, the McKinsey Global Institute predicts “exponential growth in data for the foreseeable future” in a 2011 report.
- Syracuse University - M.S. in Applied Data Science: GRE Waivers available
- SMU - Master of Science in Data Science - Bachelor's Degree Required.
- UC Berkeley - Master of Information and Data Science Online - Bachelor's Degree Required.
- Syracuse University - Master of Information Management Online
- Villanova Business - Master's in Analytics and Study Data Mining, Predictive Analytics Online
According to the Providence Journal, Rhode Island’s Governor touted the state’s data science and computer science workforce in a pitch to lure GE to Providence in early 2016. Rhode Island has a number of qualities that make it attractive to high tech businesses looking to set up East Coast operations, including one of the highest R&D tax credits in the country, pension reform, and an optimal location between Boston and New York City.
Both private companies and public agencies in Rhode Island have high-powered data analysis centers in the state. 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 numerous opportunities for employment as a data scientist 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.
Undergraduate Degree and Master’s Prerequisite Courses
Graduate schools that offer data science programs look for students who have the appropriate background for this field. Such preparation entails:
- 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
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, coding, hacking, programming, or data mining
- 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
It is imperative to perform high quality work with an employer to secure the laudatory letters of recommendation that are 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, and students who have taken the exams strongly recommend working through sample math problems from the practice tests available until the candidate is highly comfortable with them.
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®.
Closing Gaps in Functional Knowledge Through MOOCs and Bridge Courses
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 that are designed to supplement education before applying to a master’s program.
Bridge courses 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 is no exception to the national trend of academic institutions actively working to develop new graduate programs in data science. With no campus programs specific to data science currently available through campus locations in Rhode Island, online programs have become the standard 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
- Scaling data – macro and micro
- Data storage and retrieval
- 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
- Quantifying materials
- Advanced managerial economics
- Ethics and law for data science
Key Competencies and Objectives
Master’s programs in data science will equip their graduates with a wide array of proficiencies in core areas that will enable these data scientists to apply their training to a number of core areas:
- Data mining and machine learning
- Data and network security
- Data collection and analysis
- Data cleansing
- Statistical sampling
- Research design
- Database management and file organization
- Communication and visualization
- Programming languages such as Python and C++
- Ethics, privacy, and relevant law
Career Opportunities for Data Scientists in Rhode Island with Advanced Degrees
Rhode Island offers numerous 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. Shown below are job listings for data science positions in Rhode Island that were compiled in February 2016. 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 professional 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 is 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 – The successful candidate will 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.