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Data Analytics Jobs in Clemson, SC (NOW HIRING)

Financial Analyst

Anderson, SC ยท On-site

$75K - $85K/yr

This role is ideal for someone who enjoys turning financial data into clear business insights ... Perform ad hoc financial analysis and data review to support decision-making, budgeting, and ...

Collections Strategy Manager

Greenville, SC ยท On-site

$120K - $145K/yr

This role will leverage advanced data analytics and segmentation techniques to design, test, and optimize collections strategies that improve customer outcomes while ensuring compliance with ...

Business Analytics Tutor

Greenville, SC ยท Remote

$18 - $40/hr

Deep knowledge of descriptive analytics, predictive modeling, prescriptive analytics, data visualization, regression analysis, decision trees, optimization, simulation, database querying, and data ...

Finance Analyst

Anderson, SC ยท On-site

$50K - $70K/yr

Maintain cost accounting data in ERP systems * Ensure internal controls over financial reporting ... Strong analytical and problem-solving abilities * Attention to detail and accuracy * Ability to ...

Finance Analyst

Anderson, SC ยท On-site

$24.04 - $33.65/hr

Maintain cost accounting data in ERP systems * Ensure internal controls over financial reporting ... Strong analytical and problem-solving abilities * Attention to detail and accuracy * Ability to ...

Key Responsibilities Pricing Strategy & Analytics * Build and maintain comprehensive pricing models ... Strong aptitude for data analysis, consumer psychology, and mathematical forecasting.

Key Responsibilities Pricing Strategy & Analytics * Build and maintain comprehensive pricing models ... Strong aptitude for data analysis, consumer psychology, and mathematical forecasting.

Showing results 41-60

Data Analytics information

See Clemson, SC salary details

$20

$46

$80

How much do data analytics jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for data analytics in Clemson, SC is $46.39, according to ZipRecruiter salary data. Most workers in this role earn between $37.26 and $52.55 per hour, depending on experience, location, and employer.

What kind of jobs can you get with data analytics?

Data analytics skills can lead to roles such as data analyst, business analyst, data scientist, and data engineer. These jobs involve analyzing data to support decision-making, creating reports, and developing data models using tools like SQL, Excel, and Python or R. Strong analytical skills and knowledge of data visualization are essential for these positions.

Is a data analyst still a good career?

Data analysts remain in high demand across industries due to the increasing reliance on data-driven decision making. Strong skills in tools like Excel, SQL, and visualization software, along with certifications, can enhance job prospects and career growth in this field.

How does a data analytics professional typically collaborate with other departments within an organization?

Data Analytics professionals frequently work alongside teams such as marketing, finance, operations, and product development to identify trends, solve business problems, and inform strategic decisions. Collaboration often involves gathering data requirements, interpreting findings, and presenting actionable insights in a clear and accessible manner. Effective communication and the ability to translate technical data into business terms are essential for ensuring recommendations are implemented and drive measurable impact. Regular cross-functional meetings and project-based teamwork are common, offering opportunities to learn from other disciplines and broaden one's organizational influence.

What jobs can a data analyst do?

A data analyst can work in roles such as business analyst, data specialist, or reporting analyst, focusing on collecting, processing, and analyzing data to support decision-making. They often use tools like Excel, SQL, and data visualization software, and may work in industries like finance, healthcare, marketing, or technology. Strong analytical skills and knowledge of statistical methods are essential for these positions.

What is the work for a data analytics?

A data analyst's work involves collecting, processing, and analyzing data to identify trends, support decision-making, and improve business outcomes. They use tools like Excel, SQL, and data visualization software, and often require strong analytical skills and attention to detail.

What is data analytics?

Data analytics is the process of examining raw data to uncover trends, patterns, and insights that can inform decision-making. Professionals in this field use statistical techniques, programming, and data visualization tools to interpret complex data sets. Data analytics is applied in various industries, including business, healthcare, finance, and technology, to optimize operations, improve customer experiences, and drive strategic initiatives. The field often requires knowledge of tools like Excel, SQL, Python, and specialized analytics platforms.

What is the difference between Data Analytics vs Data Analyst?

AspectData AnalyticsData Analyst
Role FocusAnalyzing large datasets to identify trends and insightsInterpreting data, creating reports, and supporting decision-making
Skills & CertificationsStatistical skills, data visualization, tools like SQL, Python, RData visualization, Excel, SQL, basic statistical knowledge
Work EnvironmentOften in data teams, tech companies, or consulting firmsBusiness units, marketing, finance, or operations teams
Common UsageRefers to the field or disciplineRefers to the job role or position

While both roles involve working with data, Data Analytics typically refers to the broader field or discipline focused on analyzing data to extract insights. A Data Analyst is a specific job role within that field, responsible for interpreting data, creating reports, and supporting business decisions.

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

To thrive as a Data Analytics professional, you need strong quantitative analysis skills, proficiency in statistics, and a relevant degree such as in mathematics, computer science, or a related field. Experience with technical tools like SQL, Python or R, data visualization platforms (e.g., Tableau, Power BI), and sometimes certifications like Google Data Analytics or Microsoft Certified: Data Analyst Associate are highly valuable. Critical thinking, problem-solving, and effective communication are essential soft skills for interpreting data and presenting findings to stakeholders. These skills and qualities are crucial for transforming raw data into actionable insights that drive business decision-making.
What are the most commonly searched types of Data Analytics jobs in Clemson, SC? The most popular types of Data Analytics jobs in Clemson, SC are:
What job categories do people searching Data Analytics jobs in Clemson, SC look for? The top searched job categories for Data Analytics jobs in Clemson, SC are:
What cities near Clemson, SC are hiring for Data Analytics jobs? Cities near Clemson, SC with the most Data Analytics job openings:
Infographic showing various Data Analytics job openings in Clemson, SC as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 13% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $96,484 per year, or $46.4 per hour.

Senior Analytics Engineer

World Acceptance Corporation

Greenville, SC โ€ข On-site

$98K - $134K/yr

Full-time

Posted 3 days ago

New


Job description

We're adding a dedicated engineer to our Operations Analytics team to close a specific gap: the space between raw, platform-grade data and the trusted, business-ready datasets our analysts and marketers rely on. You'll build and own the analytics data layer - curated models, marts, and metrics, including rewriting and migrating existing SQL Server models into Snowflake - on top of the base tables maintained by the IT Data Engineering team, and you'll make sure those data products are accurate, reliable, well documented, and prioritized around what the business actually needs.
This is a hands-on engineering role with an analyst's instincts and a communicator's temperament. You will not work in isolation: you're the technical translator who lets Analytics move fast and keeps us aligned with Data Engineering's platform, standards, and guardrails.

Essential Duties and Responsibilities:

Build the analytics data layer

  • Model trusted, reusable datasets- design and build curated tables, marts, and a semantic/metrics layer on top of the platform's base tables, so the whole team reports on the same definitions.
  • Turn business questions into data products- translate what Analytics and Marketing need into performant, well-tested SQL and documented datasets.
  • Write engineering-grade code- version-controlled, peer-reviewed, and built to the team's standards, not one-off scripts.
  • Migrate & modernize- rewrite and migrate existing SQL Server data warehouse/data store models, stored procedures, and jobs into Snowflake, following the team's patterns and standards.

Own reliability, quality & accuracy

  • Build the checks that catch problems first- freshness, volume, schema, and business-rule validation so issues are caughtbeforethey reach reports, customers, or campaigns.
  • Take ownership of critical recurring data products- the scheduled jobs, stored procedures, and models behind high-stakes processes (e.g., incentive-compensation calculations) - treating them as products with clear owners, SLAs, monitoring, alerting, and runbooks, built to run reliably rather than patched.
  • Validate business accuracy- because you understand the data and the business, you can stand behind the numbers.

Bridge, communicate & enable

  • Be the translator- represent Analytics' priorities to Data Engineering and bring engineering discipline back to Analytics; speak both languages fluently.
  • Make data self-serve and trusted- document datasets, definitions, and lineage; enable and coach analysts so they can build confidently on your models.
  • Communicate exceptionally- explain technical trade-offs to non-technical stakeholders clearly, and keep partners informed on status, risks, and timelines.
  • Mind performance and cost- write efficient queries and manage warehouse usage within the platform's cost and governance guardrails.

Education and/or Experience:

  • 5+ yearscombined experience across data engineering and analytics - genuinely strong on both sides, not one with a passing knowledge of the other.
  • Strong analytical judgment- you can explore data, figure out what it actually means, and turn ambiguous business questions into clear, defensible answers, not just build to spec.
  • Advanced SQLand hands-ondata modeling(dimensional models, marts, semantic layers).
  • Experience with acloud data warehouse(Snowflake preferred) and atransformation framework(e.g., dbt or equivalent).
  • SQL Server / T-SQL and Python- hands-on across an existing SQL Server data warehouse/data store, including migrating and rewriting its objects into Snowflake.
  • Comfort withorchestration(e.g., Airflow) andversion control / CI/CD(Git; Azure DevOps a plus).
  • Experience building or supportingBI/reporting(Power BI preferred).
  • Exceptional communicationand stakeholder partnership - a track record of translating between business and technical teams.
  • Demonstrated ownership ofdata quality and reliability(monitoring, validation, SLAs).
  • Financial services / consumer lending domain experience; comfort with regulated data (GLBA, PII handling).
  • Experience embedded in a business team while partnering with a central platform/DE group.
  • Experience migrating SQL Server / T-SQL workloads to Snowflake at scale.
  • Familiarity with data catalog / lineage and cost-management practices on Snowflake.
  • A habit of documentation and enablement - you make others better with data.

Physical Demands:

  • Must be able to constantly remain in a stationary position.
  • Constantly operates a computer and other office productivity machinery, such as a calculator, copy machine, and computer printer.
  • Occasionally may require light lifting to 25 pounds.

Work Environment:

  • Office environment.
  • Occasional travel may be required.

This job description reflects management's assignment of essential functions; and nothing in this herein restricts management's right to assign or reassign duties and responsibilities to this job at any time.

It is the policy of World Acceptance Corporation to provide equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state or local law. In addition, World Acceptance Corporation will provide reasonable accommodations for qualified individuals with disabilities.