Find & Apply For Data Scientist Jobs In Greenville, South Carolina
Data Scientist jobs in Greenville, South Carolina involve analyzing data to extract insights, build predictive models, and drive decision-making processes. Responsibilities include cleaning and organizing data, developing algorithms, and communicating findings to stakeholders. Strong skills in programming, statistics, and machine learning are essential for success in this role. Below you can find different Data Scientist positions in Greenville, South Carolina.
Jobs in Greenville
Browse jobs from a variety of sources below, sorted with the most recently published, nearest to the top. Click the title to view more information and apply online.
Model Validation Analyst
United Community Bank, N.A.
Greenville, SC
Data Scientist III (US)
TD Bank
Greenville, SC
Data Scientist II (US)
Td Securities USA
Greenville, SC
Data Scientist II (US)
TD Bank
Greenville, SC
Model Validation Analyst
Peoples Bank
Greenville, SC
Latest Jobs in Greenville
Salary Information & Job Trends In this Region
Data Scientists in Greenville, South Carolina play a crucial role in analyzing and interpreting complex data to inform business decisions. - Junior Data Scientist salaries range from $60,000 to $75,000 per year - Mid-level Data Scientist salaries range from $80,000 to $100,000 per year - Senior Data Scientist salaries range from $110,000 to $130,000 per year The history of Data Science in Greenville dates back to the early 2000s when companies started realizing the potential of data-driven decision-making. The demand for data scientists grew as businesses sought to gain a competitive edge through analytics. Over the years, the role of a Data Scientist in Greenville has evolved to encompass not only data analysis but also machine learning, artificial intelligence, and predictive modeling. Data scientists are now expected to have a deep understanding of statistics, programming, and domain knowledge. Current trends in Data Science in Greenville include the increasing use of big data analytics, the adoption of cloud computing for data storage and processing, and the integration of AI and machine learning algorithms into business processes. Data scientists are also focusing on data ethics and privacy concerns in their work.