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Data Analyst Jobs in Kingstree, SC (NOW HIRING)

SANTEE COOPER

DATA SCIENTIST

Moncks Corner, SC · On-site

$75K - $94K/yr

... analytics solutions that blend machine learning, simulation, and optimization to improve ... The Data Scientist leads end-to-end delivery of moderately complex projects (e.g., improved load ...

All JobsData Analyst JobsData Analyst Jobs in Kingstree, SC

Data Analyst information

See Kingstree, SC salary details

$29.3K

$71.3K

$117.4K

How much do data analyst jobs pay per year?

As of Aug 28, 2026, the average yearly pay for data analyst in Kingstree, SC is $71,322.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,900.00 and $83,700.00 per year, depending on experience, location, and employer.

What does a data analyst do?

A Data Analyst is responsible for collecting, processing, and analyzing data to help organizations make informed business decisions. They use statistical tools and software to interpret data sets, identify trends, and create visual reports. Data Analysts often collaborate with other departments to provide actionable insights and support strategic planning. Their work helps organizations optimize operations, track performance, and solve business problems using data-driven approaches.

What are the key skills and qualifications needed to thrive as a data analyst, and why are they important?

To thrive as a Data Analyst, you need strong analytical skills, proficiency in statistics, and a relevant degree such as in mathematics, statistics, or computer science. Familiarity with data analysis tools like SQL, Excel, Python or R, and experience with visualization platforms such as Tableau or Power BI are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help analysts interpret data insights and present findings clearly to stakeholders. These skills are crucial for transforming raw data into actionable business insights that drive informed decision-making.

What are some common challenges data analysts face when working with large datasets, and how are they typically addressed?

Data Analysts often encounter challenges such as data quality issues, missing or inconsistent values, and slow processing times when handling large datasets. These challenges are typically addressed by implementing data cleaning routines, using advanced data management tools, and leveraging programming languages like Python or R for efficient data manipulation. Collaboration with database administrators and IT teams is also common to ensure data integrity and optimize data storage solutions. Staying updated with best practices in data wrangling and visualization helps Data Analysts deliver accurate and actionable insights.

What is the difference between Data Analyst vs Data Scientist?

AspectData AnalystData Scientist
Required CredentialsBachelor's degree in statistics, mathematics, or related field; often certifications in data analysis toolsBachelor's or master's in computer science, statistics, or related; often advanced certifications or degrees
Work EnvironmentBusiness settings, focusing on data reporting and visualizationResearch and development environments, focusing on predictive modeling and complex algorithms
Employer & Industry UsageRetail, finance, healthcare, and marketing companiesTech firms, research institutions, and large enterprises

While both roles analyze data, Data Analysts primarily focus on interpreting existing data to generate reports and insights, whereas Data Scientists develop predictive models and advanced algorithms to forecast trends and solve complex problems.

Do data analysts get paid well?

Data analysts typically earn competitive salaries that vary by experience, location, and industry. Entry-level positions may start lower, but with skills in tools like Excel, SQL, and data visualization, salaries tend to increase with expertise and certifications. Overall, data analysis is considered a well-paying field with growth potential.

Is it hard to get a data analyst job?

Securing a data analyst position can be competitive, as it often requires strong skills in data manipulation, statistical analysis, and proficiency with tools like Excel, SQL, or Python. Candidates with relevant education, certifications, and experience tend to have better chances, but persistence and continuous skill development are important.

What work does a data analyst do?

A data analyst collects, processes, and analyzes large datasets to identify trends, patterns, and insights that support business decision-making. They use tools like Excel, SQL, and data visualization software to interpret data and communicate findings to stakeholders. Strong analytical skills and attention to detail are essential for this role.
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What are the most commonly searched types of Data Analyst jobs in Kingstree, SC?

The most popular types of Data Analyst jobs in Kingstree, SC are:

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The top searched job categories for Data Analyst jobs in Kingstree, SC are:

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Data Analyst jobs near you
Infographic showing various Data Analyst job openings in Kingstree, SC as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $71,322 per year, or $34.3 per hour.

DATA SCIENTIST

SANTEE COOPER

Moncks Corner, SC • On-site

$75K - $94K/yr

Full-time

Re-posted 7 days ago

Santee Cooper rating

7.4

Company rating: 7.4 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

Job description

Position Description:
This position is responsible for independently designing, implementing, and productionizing advanced analytics solutions that blend machine learning, simulation, and optimization to improve operational decision-making at Santee Cooper. The Data Scientist leads end-to-end delivery of moderately complex projects (e.g., improved load forecasting, asset health surrogate models, scheduling/dispatch optimizers), owns model quality and lifecycle, and partners closely with operations to deploy and monitor models in production with measurable business impact.
Essential Job Tasks:
  • Leads end-to-end development of ML/DL models for forecasting, anomaly detection, classification, or surrogate modeling; evaluate trade offs and select appropriate algorithms.
  • Designs and implement mid complexity optimization models (MILP/heuristics) and integrate them with learned models to support decision workflows (maintenance scheduling, dispatch, demand response).
  • Develops simulation experiments and digital twin style workflows for scenario analysis and capacity planning.
  • Build robust feature engineering pipelines and collaborate with data engineering to productionize datasets (feature stores, incremental pipelines).
  • Applies and extends LLM capabilities for automation tasks (intelligent assistants, summarization, data augmentation) using safe prompt engineering and light fine-tuning where appropriate.
  • Implements MLOps best practices: automated training, model versioning, CI/CD, monitoring, and alerting for drift/performance.
  • Performs rigorous model validation: back testing, cross validation, uncertainty quantification, sensitivity analyses, and test data holding strategies.
  • Documents models, assumptions, and provide reproducible artifacts and dashboards for stakeholders.

*Will consider Data Scientist I or II
Position Requirements:
Data Scientist I
  • Bachelor's degree in Mathematics, Statistics, Computer Science or related field.

Compensation Information:
$75,500 - $94,350 (min. - mid.)
Data Scientist II
  • Bachelor's degree in Mathematics, Statistics, Computer Science or related field + 2 years experience as an ETL Developer and/or Data Analyst.
  • Must be proficient in Python (pandas, NumPy, scikit-learn; plus PyTorch/TensorFlow for DL; FastAPI/Flask for services; venv/poetry) and working familiarity with R for analysis when needed.

Compensation Information:
$84,180 - $105,210 (min. - mid.)

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