Online Master's in Data Science for Jobs in Montana

Data science has applicants in virtually every field in Montana, exemplified in winter sports at the Big Sky Resort one hour south of Bozeman. Snowfall, including the type of snow (wet, dry, sticky, powder) translates directly into revenue and economic survival for resorts like Big Sky, who see the many-fold opportunities for return as being well-worth an investment in qualified data scientists.

If super-computer weather forecasting wasn’t challenging enough, data scientists at places like Big Sky Resort combine factors like the weather, ocean temperatures and currents, elevation, and temperature with how these relate to customer behavior patterns to optimize things like resort services, staffing, and supply levels. The ability to make accurate models that predict and respond to customer preferences translates into the potential for millions in profit at Big Sky, as well as better customer satisfaction – all made possible by data scientists.

Other sectors that are vital to Montana like healthcare, government, and transportation can be equally advantaged with the skills of qualified data scientists. This helps to explain the great demand for these professionals throughout the state and nation, as well as the growing number of academic programs offering a master’s degree in data science.

Preparing for a Master’s Degree in Data Science

As one of the most competitive academic fields out there, data science master’s programs prefer or demand their would-be students to come from a strong background, academically and professionally.

Undergraduate Degree and Master’s Prerequisite Courses

Ideally students would start preparing for master’s-level studies in data science as undergraduates, and earn a bachelor’s degree in a quantitative field such as applied mathematics, statistics, engineering, or computer science. A student’s GPA should be at least 3.0, and undergraduate coursework should include prerequisites like:

  • Linear algebra
  • Calculus I and II
  • Quantitative methods
  • Statistics
  • Programming languages

Relevant Personal and Work Experience for Admissions

Prospective students are also preferred – if not required – to come from a professional background that includes at least five years of highly relevant work experience that demonstrates mastery of quantitative skills.

Relevant professional experience could potentially be gained through many avenues in Montana:

  • With an important hub in Billings, the Burlington Northern Santa Fe Railway hires data analysts to determine the most efficient transportation routes based on factors such as weight, load size, train car availability, and personnel
  • Medical providers such as Saint James Healthcare in Butte and Saint Peters Hospital in Helena employ data technicians and infection control analysts to ensure patient outcomes are maximized in the most efficient and effective ways
  • Government agencies such as the City of Great Falls and State of Montana employ network analysts and IT maintenance professionals to analyze problems, troubleshoot solutions, and maintain network security

Applicants can supplement their professional experience with personal experience in related subjects such as:

  • Coding
  • Database administration
  • Data mining
  • Hacking
  • Mathematics or statistics

Preparing to Score Within the 85th Percentile on the GRE/GMAT Exams

Graduate programs will specify which of these exams they require, and students should aim to score in at least the 85th percentile of either the GRE or GMAT. Candidates can prepare for these exams with a variety of pre-testing resources.

The Graduate Record Exam (GRE) revised general test’s quantitative reasoning section covers the following subjects:

  • Data analysis, covering topics like statistics, standard deviation, interquartile range, tables, graphs, probabilities, permutations, and Venn diagrams
  • Arithmetic topics including integers, factorization, exponents, and roots
  • Algebraic topics such as algebraic expressions, functions, linear equations, quadratic equations, and graphing
  • Geometry, including the properties of circles, triangles, quadrilaterals, polygons, and the Pythagorean theorem

Students can prepare for the quantitative reasoning section with resources such as:

The GRE is also offered in two relevant subject tests, covering the following topics:

Physics – physics test practice book

  • Classical mechanics
  • Electromagnetism
  • Optics and waves
  • Thermodynamics
  • Statistical mechanics
  • Quantum mechanics
  • Atomic physics
  • Special relativity
  • Lab methods and specialized topics

Mathematics – mathematics test practice book

  • Calculus
  • Algebra
  • Introductory real analysis
  • Discrete mathematics
  • Probability, statistics, and numerical analysis

The Graduate Management Admissions Test’s (GMAT) quantitative section covers topics that relate to data analysis. One of the four main parts of the GMAT, the quantitative section is comprised of 37 questions to be completed in 75 minutes. All questions pertain to data sufficiency and problem solving. Students can prepare for the GMAT using resources such as those provided by the Princeton Review and Veritas Prep.

Bridge Programs and Massive Open Online Course (MOOC) Options to Bolster Qualifications

Data science graduate programs may require their admitted students to complete a bridge program before enrolling in core-subject courses. Bridge programs catch students up with a core data science subject – for example engineering, programming, mathematics, statistics, or computer science – if they have any holes in their academic history. These can be one course or a course series, and take place with the home university after a student is admitted. Examples of subjects covered can include:

Fundamental bridge programs:

  • Algorithms
  • Linear algebra
  • Data structures

Programming Bridge Programs

  • Programming in languages like Python, JAVA, C++, and R

MOOCs are online courses whose content contains recorded lectures by preeminent professors, sample problem sets, and interactive user forums. MOOCs allow students to interact with each other as well as with participating teaching assistants and professors over the web. Students can find MOOCs in any number of subjects, including data science, mathematics, programming languages, physics, and engineering. While MOOCs may be academically rigorous, data science graduate programs do not recognize these as accredited education.

Earning a Master’s Degree in Data Science

Like most other states in the nation, Montana is still catching up with the emerging field of data science. While graduate-level degrees and certificates are currently not available at schools in Montana, students can find some relevant undergraduate resources:

  • Bachelor’s of Science (BS) in Statistics, with a concentration in data science – Butte
  • Big Data Analytics Certificate – Missoula
  • Cyber Security Professional Certificate (undergraduate) – Missoula

To earn the full advantages that come with a master’s degree in data science students can consider going out-of-state or completing their education online. Colleges and universities offering a master’s in data science online provide students with a convenient class schedule and flexible completion options:

  • Traditional completion time – approximately 18 months or three semesters
  • Accelerated completion – completion in as little as 12 months or two semesters
  • Part-time – completion in as much as 32 months or five semesters
  • Graduate certificate – can be completed in one to two semesters; approximately 12-15 semester credits

Graduate programs are approximately 30 semester credits, and students can choose from several types of relevant degrees:

  • Master of Science (MS) in Data Science
  • Master of Information and Data Science (MIDS)
  • Master of Science in Data Science (MSDS)
  • Data Mining and Applications Graduate Certificate
  • Online Graduate Certificate in Data Science

Core Curriculum

Graduate degrees in data science cover core topics such as:

  • Experimental statistics
  • Data research design and applications
  • File organization and database management
  • Data storage and retrieval
  • Network and data security
  • Experiments and casual inference
  • Machine learning and artificial intelligence
  • Information visualization
  • Statistical sampling
  • Ethics and law for data science
  • Data mining
  • Quantifying materials
  • Scaling data – macro and micro
  • Advanced managerial economics
  • Applied regression and time series analysis
  • Visualization of data
  • Immersion

Programs culminate with an immersion experience, where students work on an actual project in teams to achieve concrete goals. In addition to evaluating core data science principles, professors and potential employers also rate students on their ability to work together.

Key Competencies and Objectives

Students who earn their master’s degree in data science should be able to exhibit these core competencies and apply them in the workplace:

  • Teamwork to achieve specific goals
  • Interpretation and communication of results
  • Development and implementation of sophisticated data analyses
  • Programming languages such as GitHub, SAS, Python, and Shiny by Rstudio
  • Ability to conduct database queries
  • Familiarity with hash algorithms, cyphers, and secure communications protocols
  • Ability to conduct association mining and cluster analysis
  • Data survey management and implementation
  • Development of innovative design and research methods

Career Opportunities in Montana for Graduate-Prepared Data Scientists

Whether it’s analyzing wildlife health and numbers in Glacier National Park or developing models for snowfall and snow quality, data scientists can find their services in demand with a small startup in Bozeman or the federal government’s Bureau of Land Management.

Crunching numbers to develop useful models can be exemplified by the specifics that come out of snowfall forecasting at Big Sky. Factors considered in model development include:

  • El Nino or La Nina – in these years snowfall ranges between 97-112 percent of normal
  • Elevation of weather stations – 8,900 feet, 9,000 feet, and 9,600 feet
  • Wind speed and direction
  • Snowfall and snow-water equivalent
  • Temperature – average 25 Fahrenheit
  • Customer behavior – a factor that requires an entirely new predictive model and data

The following job listings are shown as illustrative examples only and are not meant to represent job offers or assurances of employment. These examples were taken from a survey of job vacancy announcements for data scientists in Montana, completed in March 2016. The field of data science is so new that companies list requirements that specify a master’s degree in, “a quantitative field.” Many of today’s candidates with graduate degrees did not have the option of obtaining a master’s degree in data science since graduate programs specific to the field were not yet developed.

Manager II of Predictive Analytics Application Development with BNSF in Billings

  • Working within Burlington Northern Santa Fe Railway’s predictive analytics department, this incumbent uses their strong technical background in big data to improve the efficiency of transport
  • Job duties include developing a technology strategy for predictive analytics, developing cross-functional relationships with business intelligence and information management, and creating an environment that fosters innovation
  • Applicants must have at least five years of relevant big data work experience and an undergraduate degree; a master’s degree in a relevant field may substitute for some years of work experience

Biological Science Technician (GS-07) with the Bureau of Land Management in Missoula

  • Incumbents in this position are responsible for conducting inventories, studies, and data analysis to create an informed report for the Department of the Interior
  • Duties include conducting marine life inventories and water quality samplings, plus the analysis and aggregation of data from these fields
  • Applicants must have at least the equivalent of one year of graduate studies in a field such as statistics, mathematics, physics, or biology

Software Engineer with Neuralynx in Bozeman

  • Incumbents will work with Neuralynx’s engineering group to create software that helps scientists understand how the brain works
  • Candidates must be detail oriented and able to communicate well, as they carry out their duties that include software test automation, application of current technology, and understanding of clinical research
  • Applicants should have the equivalent of a master’s degree in computer engineering or computer science

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