Data scientists provide crucial technical services within virtually every industry in Connecticut, including finance and banking, healthcare and biotechnology, manufacturing and logistics, retail and HR, the public sector and beyond. Executive recruiting firm Burtch Works reported in 2015 that the hiring market for analytics professionals and data scientists has gone into overdrive, citing the lack of qualified professionals in many sectors. McKinsey and Company has projected that by 2018, the US will face a shortage of analytical professionals with a 50%-60% gap between supply and demand. According to Forbes, in 2014 the five leading industries requiring big data expertise were professional, scientific and technical services; information technologies; manufacturing; retail trade and sustainability; and waste management and remediation services.
- 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
- Maryville University - Master of Science in Business Data Analytics
- Villanova Business - Master's in Analytics and Study Data Mining, Predictive Analytics Online
Data scientists in Connecticut may also seek employment in health services or finance and banking. Hartford Health Care in Hartford, CT employs a team of data scientists to manage internal data. At Hartford Health, data scientists mine hospital data, keeping records of clients and treatments, and develop statistical analysis plans for clinical research projects. Data scientists may also choose to work in the financial industry for services such as Voya Financial, located in Windsor, CT. In the financial sector, data scientists will mine and analyze data as well as identify opportunities to improve business processes by publishing reports for company executives. In the financial realm, data scientists will also use predictive modeling to integrate big data sources.
Earning a master’s degree in data science allows professionals to earn a higher salary and pursue management opportunities. Burtch Works reported the median salary for a junior level data scientist is $91,000, but data scientists who manage a team of ten or more earn salaries of $250,000 or more. Pursuing a master’s degree in data science in Connecticut is an excellent option for professionals seeking an increases earning potential and marketability.
Preparing for a Master’s Degree in Data Science in Connecticut
Candidates seeking a master’s degree in data science must meet certain minimum requirements in order to be admitted to a master’s program. Admissions departments look for candidates with excellent educational history, related employment experience, and fundamental knowledge of key data science concepts. Master’s programs maintain a set of highly selective standards, and candidates must be prepared with relevant skills, prerequisite courses, scores in the top 15 percentile on graduate entrance exams, and between 5-7 years of related work experience.
Undergraduate Degree and Master’s Prerequisite Courses
Applicants to data science master’s programs are required to meet certain minimum qualifications before gaining entrance to the program. These requirements include:
- Bachelor’s degree in a related field such as statistics, computer science, engineering, or applied math
- Minimum of 3.0 GPA during undergraduate studies
Applicants must complete prerequisite courses before enrolling in the program. Required perquisites include the following:
- Calculus I & II
- Linear algebra
In addition to completing these prerequisite courses, candidates for master’s programs will be required to demonstrate a working knowledge of quantitative concepts, score in the 85th percentile on either the GRE or GMAT exam, and have 5-7 years of work experience in data science or a related field.
Master’s program courses will require students to have a fundamental knowledge of certain concepts from undergraduate education and work experience. These concepts include:
- Data structures
- Algorithms and analysis of algorithms
- Linear algebra
Scoring Well on the Quantitative Sections of the GRE/GMAT Exams
Master’s programs maintain a selective requirement for applicants to score in the top 15 percent on the quantitative section of either the GRE or the GMAT. Admissions departments also look for excellent verbal and writing scores, expecting applicants to possess excellent communication skills.
The General Record Exam (GRE) exam’s quantitative section will evaluate the candidate’s abilities to analyze data and solve basic arithmetic, algebra, and geometry problems. The quantitative section also includes problems in statistics, standard deviation, tables, graphs, and probabilities. Candidates can prepare for the exam by reviewing sample questions and free practice exams on the official GRE website. Candidates may also prepare by reviewing a preparation guide for the quantitative section of the GRE.
The General Management Admissions Test (GMAT) also has a quantitative section which will evaluate the student’s ability to problem solve and analyze data. To prepare for the GMAT, candidates may download two free practice exams through the official GMAT website. In addition, students may take practice exams hosted through The Princeton Review and Veritas Prep. The GMAT measures the candidate’s ability to problem solve and analyze data through 37 quantitative questions.
Prior Relevant Work Experience
Most data science master’s programs will require students to possess 5-7 years of prior work experience, looking for candidates who are already familiar with the data science field. The following skills are expected by admissions departments:
- Strong communication skills
- Programming proficiency and prior experience with languages such as JAVA, C++, and Python
- Coding skills
- Hacking skills
- Data mining
- Database administration proficiency
In Connecticut, data scientists can gain the required experience through many different avenues. Some examples include:
- A data scientist with United Technologies in East Hartford, CT, working on a team of data scientists taking on challenges in machine learning, deep learning, data mining, and human computer interaction.
- An associate data scientist with The Hartord in Hartford, CT, working on a team supporting commercial markets through class plan development, advanced pricing, underwriting research, operations research, marketing analytics and product innovation.
- Data scientist or programmer at local government offices or local nonprofits.
Bridge Programs and Massive Open Online Course (MOOC) Options for Master’s Program Applicants Who Need to Fill Gaps in Functional Knowledge
Candidates applying to data science master’s programs may not possess each required skill for applicants. In this case, most master’s programs offer bridge programs to potential students. Bridge programs help students learn fundamental skills in an accelerated time period. They are offered in two areas:
- Fundamental programs, including linear algebra, algorithms and algorithm analysis, and data structures
- Programming bridge programs, including languages such a Python, JABA, and C++
Bridge courses consist of about half the course load of regular master’s classes, but students must compete the bridge course before moving forward into core coursework.
Massive Open Online Courses (MOOC) are online-hosted educational programs that offer master’s students another avenue to supplement their education. MOOCs include online problem modules, filmed lectures, and the opportunity to interact with instructors and teaching assistants.
Earning a Master’s Degree in Data Science in Connecticut
Connecticut offers a handful of traditional in-state, on campus master’s programs in data science. However, more and more master’s students are choosing to enroll in online programs, citing benefits such as flexibility around a professional schedule and more diverse program options. Online programs offer fully accredited curriculum recognized by the US Department of Education as well as professional data science associations nationwide.
Programs are offered through full time, part time, and accelerated tracks. Full time options can be completed in 18 months, part-time programs can be completed in 32 months, and accelerated options can be completed in as little as 12 months. Most programs, including online options, require an immersion experience for students in their last semester. The immersion experience is a group project designed to simulate real-world data mining and analysis.
Students may choose from several different degree options:
- Master of Information and Data Science (MIDS)
- Master of Science in Data Science (MSDS)
- Graduate Certificate in Data Science
- Data Mining and Applications Graduate Certificate
Curriculum Content and Core Coursework
Coursework within master’s programs will vary, but all core courses will rely on fundamental data science concepts. The following topics will be included in most core coursework:
- Data mining
- File organization and database management
- Data storage and retrieval
- Applied regression and time series analysis
- Advanced managerial economics
- Scaling data – macro and micro
- Quantifying materials
- Ethics and law for data science
- Network and data security
- Visualization of data
- Experimental statistics
- Statistical sampling
- Machine learning and artificial intelligence
- Experiments and causal inference
- Information visualization
- Data research design and applications
Key Competencies and Objectives
Data science master’s programs will prepare students for the challenges of working in the field. After graduating, students will be proficient in the following core areas:
- Communication and visualization
- Statistical sampling
- Research design
- Data mining and machine learning
- Ethics, privacy, and relevant law
- Data collection and analysis
- Data cleansing
- Programming languages such as Python, GitHub, and SAS
- Database queries
- Database management and file organization
- Data and network security
Career Opportunities for Data Scientists in Connecticut with Advanced Degrees
In Connecticut, data scientists are indispensable to almost every industry, allowing data scientists to seek occupation with a diverse range of employers. In 2015, executive recruiting firm Burtch Works announced that because of the shortage of qualified professionals, there has never been a better time to be a data scientist looking for a job.
The following job listings are shown as illustrative examples only and are not meant to represent job offers or provide any assurance of employment. These examples were taken from a survey of job vacancy announcements for data scientists in Connecticut in February 2016.
Senior Data Scientist at Pitney Bowes in Shelton, CT
- Master’s degree or seeking master’s degree in data science or another quantitative discipline
- 7 or more years of experience in applied analytical data science role
- Experience with relational and Hadoop platforms
- Exploring external datasets and internal operational data
- Producing innovative data-driven products, services and concepts
- Managing a team of data scientists and very large data sets
Senior Data Scientist at MidState Medical Center in Hartford, CT
- Master’s degree in data science or a related field
- 3 to 5 years of experience in using data in a medical field
- Designing and directing research projects for the medical center
- Developing statistical analysis plan for clinical research projects
- Presenting research to colleagues and supporting communication with team and staff
Director of Data Science & Analytics at Pfizer, Inc. in Groton, CT
- Master’s degree in data science, computer science, management science, statistics, mathematics, or engineering
- 10 or more years of experience working in data science, data analytics, or related field
- Experience working with pharmaceutical science data
- Defining, designing, and building solutions for predictive analytics, data mining, and advanced business analytics capabilities
- Locating and analyzing operational and scientific external data to help Pfizer identify insights
- Delivering data analytical services to the company