Senior Data Scientist Career

Planning and Analysis

 
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 $120,394

*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 $123,966

*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:

Growth
North Carolina315+29.1%
Nationwide10220+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: Research comprises creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of humans, culture and society, and the use of this stock of knowledge to devise new applications. It is used to establish or confirm facts, reaffirm the results of previous work, solve new or existing problems, support theorems, or develop new theories.
  • Communication Skills: The ability to convey information to another effectively and efficiently.
  • Teamwork / Collaboration: A Collaboration is a purposeful relationship in which all parties strategically choose to cooperate in order to achieve shared or overlapping objectives.
  • Problem Solving: Problem solving consists of using generic or ad hoc methods, in an orderly manner, for finding solutions to problems.
  • Creativity: Creativity is a phenomenon whereby something new and somehow valuable is formed.

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).
  • Apache Hadoop: Apache Hadoop ( ) is an open-source software framework used for distributed storage and processing of dataset of big data using the MapReduce programming model.

Distinguishing Skills

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

  • Data Engineering: Working experience of Data Engineering, which includes gathering and collectiong of data, storing it, batch processing or real-time processing of data, and setting up access via e.g. an API.
  • NumPy: Working experience of NumPy, which is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays.
  • Pipeline (Computing): Working experience of pipelines. In computing, a pipeline is a set of data processing elements connected in series, where the output of one element is the input of the next one.
  • PIG: Experience working with Apache Pig, a platform for analyzing large data sets that consists of a high-level language for expressing data analysis programs, coupled with infrastructure for evaluating these programs.
  • Apache Spark: Working experience of Apache Spark. Apache Spark is an open-source engine developed for handling large-scale data processing and analytics. Spark offers the ability to access data in a variety of sources, including Hadoop Distributed File System (HDFS), OpenStack Swift, Amazon S3 and Cassandra.

Salary Boosting Skills

A professional who wishes to excel in this career path may consider developing the following highly valued skills:

  • Long Short-Term Memory (LSTM): Working experience of Long Short-Term Memory (LSTM), which are a building unit for layers of a recurrent neural network (RNN).
  • Graph-Based Algorithms: Working experience of Graph-Based AlgorithmsGraph-Based Algorithms are a way of representing algorithms in a visual manner which can aid comprehension
  • Recurrent Neural Network (RNN): Working experience of Recurrent Neural Network (RNN). A recurrent neural network (RNN) is a class of artificial neural network where connections between units form a directed graph along a sequence. This allows it to exhibit dynamic temporal behavior for a time sequence. Unlike feedforward neural networks, RNNs can use their internal state (memory) to process sequences of inputs.
  • Time Series Analysis: Working experience of Time Series Analysis, which comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series forecasting is the use of a model to predict future values based on previously observed values. Time series analysis can be applied to real-valued, continuous data, discrete numeric data, or discrete symbolic data (i.e. sequences of characters, such as letters and words in the English language).
  • Boosting (Machine Learning): Working experience of Boosting (Machine Learning), which is a machine learning ensemble meta-algorithm for primarily reducing bias, and also variance in supervised learning, and a family of machine learning algorithms that convert weak learners to strong ones.

Education

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

.
Education Level%
Bachelor's Degree13%
Master's Degree77%
Doctoral Degree10%

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 years12%
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
  • Lead Data Scientist
  • Principal Data Scientist
  • Data Scientist II
  • Data Scientist Analyst/Data Scientist/Data Scientist Senior-Ps20287

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