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Realist?

Realist

Realists are usually interested in 'things' - such as buildings, mechanics, equipment, tools, electronics etc. Their primary focus is dealing with these - as in building, fixing, operating or designing them. Involvement in these areas leads to high manual skills, or a fine aptitude for practical design - as found in the various forms of engineering.

Realists like to find practical solutions to problems using tools, technology and skilled work. Realists usually prefer to be active in their work environment, often do most of their work alone, and enjoy taking decisive action with a minimum amount of discussion and paperwork.

Salary Range
€50k - €75k
Career Zone

In Brief...

Uses strong business acumen, coupled with an ability to communicate data findings to influence how an organisation approaches business challenges.

Knowledge

  • Computers and Electronics Knowledge of circuit boards, processors, chips, electronic equipment, and computer hardware and software, including applications and programming.
  • Mathematics Knowledge of arithmetic, algebra, geometry, calculus, statistics, and their applications.
  • English Language Knowledge of the structure and content of the English language including the meaning and spelling of words, rules of composition, and grammar.
  • Education and Training Knowledge of principles and methods for curriculum and training design, teaching and instruction for individuals and groups, and the measurement of training effects.
  • Telecommunications Knowledge of transmission, broadcasting, switching, control, and operation of telecommunications systems.

Skills

  • Complex Problem Solving Identifying complex problems and reviewing related information to develop and evaluate options and implement solutions.
  • Critical Thinking Using logic and reasoning to identify the strengths and weaknesses of alternative solutions, conclusions or approaches to problems.
  • Systems Analysis Determining how a system should work and how changes in conditions, operations, and the environment will affect outcomes.
  • Systems Evaluation Identifying measures or indicators of system performance and the actions needed to improve or correct performance, relative to the goals of the system.
  • Judgment and Decision Making Considering the relative costs and benefits of potential actions to choose the most appropriate one.

In Summary - Data Scientist

Career Sectors

Data Scientists typically work in the following Career Sectors:

Big Data
Computers & ICT
Statistics
Physics, Mathematics & Space Science
Data Analysis
Physics, Mathematics & Space Science
Maths and Your Career
Physics, Mathematics & Space Science
Statistics
Physics, Mathematics & Space Science

Videos & Interviews

Catherine Ahearn, Data Scientist

Catherine Ahearn is a Data Scientist. Her job involves researching various mathematical and machine learning techniques, and writing code to create predictive models using large amounts of data.

Videos on the Web

The Work - Data Scientist

Data scientists mainly looking at estimating the unknown, for example, building statistical models that help with making decisions based on data. A data scientist is an evolution of the business or data analyst role. Their formal training is similar. They have a solid foundation typically in the areas of computer science and applications, modeling, statistics, analytics and maths.

What sets the data scientist apart is strong business acumen, coupled with the ability to communicate findings to both business and IT leaders in a way that can influence how an organisation approaches a business challenge.

Good data scientists will not just address business problems, they will pick the right problems that have the most value to the organisation. The data scientist role has been described as “part analyst, part artist.”

Anjul Bhambhri, vice president of big data products at IBM, says, “A data scientist is somebody who is inquisitive, who can stare at data and spot trends. It's almost like a Renaissance individual who really wants to learn and bring change to an organisation."

Whereas a traditional data analyst may look only at data from a single source – a CRM system, for example – a data scientist will most likely explore and examine data from multiple, disparate sources. The data scientist will sift through all incoming data with the goal of discovering a previously hidden insight, which in turn can provide a competitive advantage or address a pressing business problem.

A data scientist does not simply collect and report on data, but also looks at it from many angles, determines what it means, then recommends ways to apply the data.

Data scientists are inquisitive: exploring, asking questions, doing “what if” analysis, questioning existing assumptions and processes. Armed with data and analytical results, a top-tier data scientist will then communicate informed conclusions and recommendations across an organization’s leadership structure.

Most commonly reported Work Tasks

  • Analyze problems to develop solutions involving computer hardware and software.
  • Assign or schedule tasks to meet work priorities and goals.
  • Evaluate project plans and proposals to assess feasibility issues.
  • Apply theoretical expertise and innovation to create or apply new technology, such as adapting principles for applying computers to new uses.
  • Consult with users, management, vendors, and technicians to determine computing needs and system requirements.
  • Meet with managers, vendors, and others to solicit cooperation and resolve problems.
  • Conduct logical analyses of business, scientific, engineering, and other technical problems, formulating mathematical models of problems for solution by computers.
  • Develop and interpret organizational goals, policies, and procedures.
  • Participate in staffing decisions and direct training of subordinates.
  • Develop performance standards, and evaluate work in light of established standards.

Most commonly reported Work Activities

  • Interacting With Computers Using computers and computer systems (including hardware and software) to program, write software, set up functions, enter data, or process information.
  • Getting Information Observing, receiving, and otherwise obtaining information from all relevant sources.
  • Processing Information Compiling, coding, categorizing, calculating, tabulating, auditing, or verifying information or data.
  • Thinking Creatively Developing, designing, or creating new applications, ideas, relationships, systems, or products, including artistic contributions.
  • Making Decisions and Solving Problems Analyzing information and evaluating results to choose the best solution and solve problems.
  • Updating and Using Relevant Knowledge Keeping up-to-date technically and applying new knowledge to your job.
  • Identifying Objects, Actions, and Events Identifying information by categorizing, estimating, recognizing differences or similarities, and detecting changes in circumstances or events.
  • Documenting/Recording Information Entering, transcribing, recording, storing, or maintaining information in written or electronic/magnetic form.
  • Communicating with Supervisors, Peers, or Subordinates Providing information to supervisors, co-workers, and subordinates by telephone, in written form, e-mail, or in person.
  • Interpreting the Meaning of Information for Others Translating or explaining what information means and how it can be used.

Interests - Data Scientist

This occupation is typically suited for people with the following Career Interests:

Investigative

The Investigative person will usually find a particular area of science to be of interest. They are inclined toward intellectual and analytical activities and enjoy observation and theory. They may prefer thought to action, and enjoy the challenge of solving problems with sophiscticated technology. These types prefer mentally stimulating environments and often pay close attention to developments in their chosen field.

Realist

Realists are usually interested in 'things' - such as buildings, mechanics, equipment, tools, electronics etc. Their primary focus is dealing with these - as in building, fixing, operating or designing them. Involvement in these areas leads to high manual skills, or a fine aptitude for practical design - as found in the various forms of engineering.

Realists like to find practical solutions to problems using tools, technology and skilled work. Realists usually prefer to be active in their work environment, often do most of their work alone, and enjoy taking decisive action with a minimum amount of discussion and paperwork.

Administrative

Administrative people are interested in work that offers security and a sense of being part of a larger process. They may be at their most productive under supervisors who give clear guidelines and while performing routine tasks in a methodical and reliable way.

They tend to enjoy clerical and most forms of office work, where they perform essential administrative duties. They often form the backbone of large and small organisations alike. They may enjoy being in charge of office filing systems, and using computers and other office equipment to keep things running smoothly. They usually like routine work hours and prefer comfortable indoor workplaces.

Entry Requirements - Data Scientist

A Bachelors degree in the areas of computer science and applications, modeling, statistics, analytics and maths.

Combined with a Masters in Business Administration (MBA) or relavent postgraduate qualification, related to the particualr industry sector .

Last Updated: October, 2014

Pay & Salary - Data Scientist

Salary Range (thousands per year)* €50k - €75k

Graduate/Starting 35
Senior/Potential (10 yrs exp) 75,000+

Data Source(s):
The Insurance Institute of Ireland / Brightwater

Last Updated: May, 2017

* The lower figures typically reflect starting salaries. Higher salaries are awarded to those with greater experience and responsibility. Positions in Dublin sometimes command higher salaries.

Labour Market Updates - Data Scientist

This occupation has been identified as a Job in Demand by the most recent National Skills Bulletin.

As with programmers, the labour market indicators examined point to an occupation in high demand with strong employment growth and evidence that employers are having difficulties filling vacancies.

National Skills Bulletin 2018

Useful Contacts - Data Scientist

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