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Data Science Jobs in Charleston, SC (NOW HIRING)

CSS, Inc

Data Scientist

Charleston, SC · On-site

Experience with data engineering, data management, or scientific data systems.Proficiency in SQL and at least once scripting language (Python or R preferred) to build data pipelines, visualize data ...

Ignite Digital

Data Analyst

Charleston, SC

$105K/yr

Bachelor's Degree in Computer Science, Information Technology, Data Science, other related field * Active DoD SECRET security clearance * Experience with DoW/NAVWAR business practices, data ...

DXC Technology

Data Engineering Lead

Charleston, SC · On-site

Collaborate with data scientists and AI teams to operationalize models and data products. * Support enterprise AI initiatives through governed, trusted, high-quality data pipelines. * Establish ...

DXC Technology

Data Engineering Lead

Charleston, SC · On-site

Collaborate with data scientists and AI teams to operationalize models and data products. * Support enterprise AI initiatives through governed, trusted, high-quality data pipelines. * Establish ...

Brookfield Properties

Senior Data Engineer

Charleston, SC · On-site

$99K - $134K/yr

In this role, the Senior Data Engineer will collaborate closely with data analysts, scientists, software engineers, and business stakeholders to improve data accessibility, performance, and ...

Brookfield Properties

Senior Data Engineer

Charleston, SC · On-site

$99K - $134K/yr

In this role, the Senior Data Engineer will collaborate closely with data analysts, scientists, software engineers, and business stakeholders to improve data accessibility, performance, and ...

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Showing results 21-40

All JobsData Science JobsData Science Jobs in Charleston, SC

Data Science information

See Charleston, SC salary details

$35.1K

$114.9K

$183.9K

How much do data science jobs pay per year?

As of Aug 15, 2026, the average yearly pay for data science in Charleston, SC is $114,861.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,200.00 and $127,300.00 per year, depending on experience, location, and employer.

Is a data scientist in high demand?

Yes, data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

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

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What does a data scientist do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
More about Data Science jobs

What are the most commonly searched types of Data Science jobs in Charleston, SC?

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For Data Science jobs in Charleston, SC, the most frequently searched job titles are:

What job categories do people searching Data Science jobs in Charleston, SC look for?

The top searched job categories for Data Science jobs in Charleston, SC are:

What cities near Charleston, SC are hiring for Data Science jobs?

Cities near Charleston, SC with the most Data Science job openings:

Data Science jobs near you
Infographic showing various Data Science job openings in Charleston, SC as of August 2026, with employment types broken down into 94% Full Time, 4% Part Time, and 2% Contract. Highlights an 90% In-person, 2% Hybrid, and 8% Remote job distribution, with an average salary of $114,861 per year, or $55.2 per hour.

Data Scientist

CSS, Inc

Charleston, SC • On-site

Full-time

Re-posted 25 days ago

Job description

CSS/RPI is seeking qualified candidates to manage, restore, and optimize three scientific databases to support long-term scientific integrity, collaboration, and public access to harmful algal bloom data at the Hollings Marine Laboratory in Charleston, SC.Experience Required:Experience with data engineering, data management, or scientific data systems.Proficiency in SQL and at least once scripting language (Python or R preferred) to build data pipelines, visualize data, and integrate within a federal cyberinfrastructure.Experience with data standards.Demonstrated experience with image processing and spatial data workflows (eg ArcGIS).Ability to implement an effective data quality assurance process, data optimization, and documentation procedures.Read, scope, author, and/or execute code of varying degrees of complexity for automation of data production, analysis, and distribution.Strong organizational skills, time management, and ability to manage multiple priorities in a dynamic environment.Effective team contributor with excellent interpersonal skills.Capable of working independently to meet project objectives and timelines.Highly Desirable Experience:Experience with ecological /environmental datasets and marine monitoring programs.Familiarity with data sharing platforms (ERDDAP, OBIS).Experience modernizing legacy systems.Demonstrated ability to work individually and as part of a team; highly effective interpersonal skills, as well as strong written and verbal communication competencies.Phytoplankton Monitoring Network (PMN) Database:Centralize and standardize disparate PMN datasets in a unified structure for archiving into ERDDAP.Develop and maintain scripts for automated data transfer between data platforms.Align datasets with Darwin Core standards to support data sharing.Coordinate with NCCOS and NCEI to advance the development of a GIS enabled data dashboard.Ensure PMN data integrity through accurate documentation, version control, backup, and quality control/quality assurance processes.Develop and maintain metadata standards to meet federal data quality requirements.Analytical Response Team (ART) DatabaseRestore and modernize legacy database systems (MS Access/SQL-based systems)Migrate data to a sustainable and scalable platform.Implement governance practices to ensure data integrity through documentation, file backup, and quality control.Intergovernmental Panel on Harmful Algal Blooms (IPHAB) Toxins DatabaseCoordinate with Ocean Biodiversity Information System (OBIS) to incorporate PMN data.Create data pipelines for automated data transfer between PMN and OBIS/IOC platforms.Support international data harmonization and interoperability efforts.At CSS, we are committed to fostering an inclusive and merit-based workplace. We provide equal employment opportunities to all individuals, ensuring that hiring and employment decisions are based on qualifications, skills, and performance. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.