Find & Apply For Data / Data Mining Analyst Jobs In York, South Carolina
Data / Data Mining Analyst jobs in York, South Carolina involve analyzing data to extract valuable insights for decision-making. Responsibilities include cleaning, organizing, and interpreting data to identify trends and patterns. Candidates should have strong analytical skills, proficiency in data mining tools, and experience in statistical analysis. Below you can find different Data / Data Mining Analyst positions in York, South Carolina.
Jobs in York
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.
Regulatory Data Analyst (Remote)
First American Financial
York, SC
Associate Data Recon Analyst – Performance & Data Recon
LPL Financial
York, SC
ETL Tester with Python
Capgemini
York, SC
Data Business Analyst (Remote)
Unclassified
York, SC
Data Business Analyst (Remote)
First American Financial
York, SC
Latest Jobs in York
Salary Information & Job Trends In this Region
Data and Data Mining Analysts in York, South Carolina play a vital role in extracting valuable insights from large datasets to inform business decisions. - Entry-level Data Analyst salaries range from $45,000 to $60,000 per year - Mid-career Data Mining Analyst salaries range from $65,000 to $85,000 per year - Senior Data Scientist salaries range from $90,000 to $120,000 per year The practice of data analysis in York, South Carolina, has its roots in the broader field of business intelligence, which began to take shape with the advent of computers and the proliferation of data in the late 20th century. Over the years, the role of Data / Data Mining Analysts in York has evolved significantly, transitioning from basic statistical analysis to complex data mining and predictive analytics, reflecting broader technological advancements and increased data availability. Current trends among Data / Data Mining Analysts in York include the use of artificial intelligence and machine learning techniques to predict trends, automate tasks, and provide deeper insights into data, as well as a growing emphasis on data privacy and ethical considerations in data usage.