Planning and Analysis Careers | Senior Data Scientist

Senior Data Scientist

Career Area: Planning and Analysis

Occupation Group: Data Analysis and Mathematics

Salary

Percentile wages tell how much a certain percentage of an overall population in a geographic area or within a given industry or field makes. The percentile wage estimate is the value of a wage below which a certain percent of workers fall.

An example would be the 25th percentile, 25 percent of workers employed in that occupation earn less and 75 percent earn more than the estimated wage value. At the 75th percentile, 75 percent of workers employed in that occupation earn less and 25 percent earn more than the estimated wage value.

A typical Senior Data Scientist earns the following wages (national and state):

State

The average salary in North Carolina for those pursuing this career is $121,332

*The salaries depicted here are representative of the range of salaries posted in job listings over the past year. Living wage in North Carolina is $30,000.

National

The average salary in the United States for those pursuing this career is $125,993

*The salaries depicted here are representative of the range of salaries posted in job listings over the past year. Living wage in North Carolina is $30,000.

What Does a Professional in this Career Do?

Utilizes skills and experience to systematically answer questions using data to provide actionable recommendations. Commonly utilizes advanced statistical analysis and machine learning techniques. Common responsibilities also include data cleaning and data management. Able to work and lead on data science projects independently. May involve management of other members of the data science team.

Employment Trends

The job demand and job growth statistics shown here were derived from job posts over the past year. Expected job growth projections are extrapolated from year-over-year job post listing history.

Job demand and job growth is expected at the following rates:

LocationGrowth
North Carolina365+29.1%
Nationwide10769+19%

Skills

A professional in this position typically utilizes the following skills in the course of everyday work in this exciting and challenging field:

Baseline Skills

The following are baseline skills every Senior Data Scientist is expected to have in order to experience success in this field:

  • Research: Experience performing creative and systematic work to understand a product, market, or customer, either before building a new solution, or to troubleshoot an existing issue
  • Communication Skills: The ability to convey information to another effectively and efficiently.
  • Teamwork / Collaboration: Experience working in collaborative efforts with a team to achieve a common goal or to complete a task in the most effective and efficient way.
  • Problem Solving: Problem solving consists of using generic or ad hoc methods, in an orderly manner, for finding solutions to problems.
  • Writing: Experience expressing business messages effectively in written form. This may include planning drafting and revising as necessary.

Specialized Skills

These skills are specific to working in this career:

  • Data Science: Data science, also known as data-driven science, is an interdisciplinary field about scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining.
  • Python: Python is a widely used high-level programming language for general-purpose programming, created by Guido van Rossum and first released in 1991.
  • Machine Learning: Machine learning is the subfield of computer science that, according to Arthur Samuel, gives computers the ability to learn without being explicitly programmed. Samuel, an American pioneer in the field of computer gaming and artificial intelligence, coined the term machine learning in 1959 while at IBM. Evolved from the study of pattern recognition and computational learning theory in artificial intelligence, machine learning explores the study and construction of algorithms that can learn from and make predictions on data such algorithms overcome following strictly static program instructions by making data-driven predictions or decisions, through building a model from sample inputs.
  • SQL: SQL ( ESS-kew-EL or SEE-kwl, Structured Query Language) is a domain-specific language used in programming and designed for managing data held in a relational database management system (RDBMS), or for stream processing in a relational data stream management system (RDSMS).
  • Predictive Models: Predictive modeling uses statistics to predict outcomes.

Distinguishing Skills

Any Senior Data Scientist that possesses the following skills will stand out against the competition:

  • MATLAB: MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment and fourth-generation programming language.
  • Big Data Analytics: Working experience of Big Data Analytics, which refers to the use of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that extract value from big data - data sets that are so voluminous and complex that traditional data-processing application software are inadequate to deal with them.
  • Econometrics: Econometrics is the application of statistical methods to economic data and is described as the branch of economics that aims to give empirical content to economic relations.
  • Graphics Processing Units (GPU): Working experience of Graphics Processing Units (GPU). A graphics processing unit (GPU) is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the creation of images in a frame buffer intended for output to a display device. GPUs are used in embedded systems, mobile phones, personal computers, workstations, and game consoles.
  • MapReduce: MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel, distributed algorithm on a cluster.

Experience

This position typically requires the following level of experience. The numbers presented in the pie charts below were derived from actual job posts over the past year. Not all job postings list experience requirements.

Experience Required%
0 to 2 years10%
3 to 5 years56%
6 to 8 years21%

Many of the programs offered through NC State are designed for working professionals who need additional credentials to enhance existing work experience.

Students who do not have the expected level of experience may wish to look into internship and employment opportunities.

Common Job Titles

It is possible to find work in this field in positions commonly listed as the following job titles:

  • Senior Data Scientist
  • Principal Data Scientist
  • Lead Data Scientist
  • Data Scientist II
  • Data Scientist, Senior

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