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Manufacturing Data Analyst Jobs in Georgia (NOW HIRING)

Position Summary The Data Analyst I - Curant Rare supports Curant Health's manufacturer-facing reporting and operational analytics for an assigned Rare program. This role is responsible for recurring ...

New

Data Security Architect

Atlanta, GA · On-site

$61.25 - $78.75/hr

... analytics platforms, ERP systems, SaaS applications, and AI/ML workloads * Architect secure data flows between enterprise IT and OT/manufacturing systems (ERP, MES, SCADA,etc.) * Partner with ...

Utilize data analytics to identify losses and track impact. Partner with Manufacturing, Quality, Engineering, Maintenance, and Process Technology teams to align initiatives to meet business ...

Utilize data analytics to identify losses and track impact. Partner with Manufacturing, Quality, Engineering, Maintenance, and Process Technology teams to align initiatives to meet business ...

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Manufacturing Data Analyst information

See Georgia salary details

$28.7K

$69.8K

$114.8K

How much do manufacturing data analyst jobs pay per year?

As of Aug 14, 2026, the average yearly pay for manufacturing data analyst in Georgia is $69,780.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,800.00 and $81,900.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a manufacturing data analyst?

To thrive as a Manufacturing Data Analyst, you need strong analytical skills, proficiency in data management, and a background in industrial engineering, statistics, or a related field. Experience with data visualization tools (such as Power BI or Tableau), statistical analysis software, and manufacturing ERP/MES systems is highly valued, as are certifications like Six Sigma. Attention to detail, problem-solving abilities, and effective communication skills help you stand out in this position. These capabilities are crucial for interpreting complex production data, improving manufacturing processes, and clearly conveying insights to cross-functional teams.

What are the typical daily responsibilities of a manufacturing data analyst?

Manufacturing Data Analysts typically spend their days collecting and interpreting data from manufacturing processes to identify trends, inefficiencies, or areas for improvement. They often collaborate with production teams and engineers to understand operational challenges, validate data sources, and implement process enhancements based on their findings. Daily tasks might include generating reports, monitoring real-time production metrics, developing dashboards, and supporting quality assurance efforts. This role is highly collaborative and plays a key part in driving continuous improvement and operational excellence within the manufacturing facility.

What is a manufacturing data analyst?

A Manufacturing Data Analyst collects, processes, and analyzes data from production processes to improve efficiency, quality, and cost-effectiveness. They work with large datasets, identify trends, and generate reports to support decision-making. Utilizing tools like SQL, Python, and BI software, they help optimize manufacturing workflows and reduce waste. Their role often involves collaborating with engineers, production managers, and IT teams to ensure data-driven improvements.

What are the most commonly searched types of Manufacturing Data Analyst jobs in Georgia?

The most popular types of Manufacturing Data Analyst jobs in Georgia are:

What cities in Georgia are hiring for Manufacturing Data Analyst jobs?

Cities in Georgia with the most Manufacturing Data Analyst job openings:

Infographic showing various Manufacturing Data Analyst job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, 1% Temporary, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $69,780 per year, or $33.5 per hour.

Full-time

Posted 2 days ago

New


Job description

Position Summary

The Data Analyst I – Curant Rare supports Curant Health’s manufacturer-facing reporting and operational analytics for an assigned Rare program. This role is responsible for recurring reporting, Power BI dashboard support, data validation, KPI and SLA monitoring, and analysis used in operational reviews and Quarterly Business Reviews (QBRs).

The Data Analyst I works with patient, referral, prior authorization, dispensing, and workflow data to provide accurate and actionable insights to program leadership and cross-functional partners. This position also partners with internal teams and client data contacts to investigate reporting questions, resolve data discrepancies, and ensure reporting deliverables are accurate, timely, and aligned with business requirements.

The ideal candidate is analytical, detail-oriented, comfortable working with data, and interested in developing their career in healthcare analytics and business intelligence.

Duties and Responsibilities

Core duties and responsibilities include the following. Other duties may be assigned based on business and program needs.

Reporting and Dashboard Management
  • Maintain, refresh, validate, and support Power BI reports and operational dashboards.
  • Produce daily, weekly, monthly, and quarterly reporting for program leadership and manufacturer reviews.
  • Monitor key program metrics, including referral volume, patient onboarding, benefit verification, prior authorization, dispensing, conversion, adherence, persistence, workflow activity, and service-level performance.
  • Create clear visualizations, scorecards, trends, and patient-level detail views that support operational decision-making.
  • Maintain documentation for report logic, source fields, refresh cadence, filters, exclusions, and known data limitations.
Data Quality, Reconciliation, and Validation
  • Validate reporting outputs against source systems and established business rules before distribution.
  • Reconcile patient counts, status classifications, dates, and KPI results across reports and reporting periods.
  • Identify potential data-quality issues and assist with investigating root causes.
  • Document reporting exceptions and coordinate with business and technical partners to support resolution.
  • Maintain organized validation files, metric definitions, and reporting documentation.
  • Escalate significant data discrepancies or reporting concerns appropriately.
Business Analysis and Operational Insights
  • Analyze patient journeys and operational workflows to identify trends and potential barriers to enrollment, therapy initiation, conversion, and refill continuity.
  • Evaluate performance across workflow steps, patient status, payer, aging, responsible party, and other relevant operational dimensions.
  • Support cohort, trend, aging, turnaround-time, and exception analysis.
  • Translate analytical findings into clear summaries for program leadership and business partners.
  • Assist with ad hoc reporting and analysis requests while maintaining consistent documentation and methodology.
QBR, Manufacturer, and Cross-Functional Support
  • Prepare validated data, exhibits, supporting details, and commentary for monthly operational reviews and Quarterly Business Reviews.
  • Partner with Patient Engagement, Pharmacy, Finance, IT, and program leadership to clarify reporting requirements and resolve reporting questions.
  • Maintain awareness of recurring reporting deadlines and support timely completion of deliverables.
  • Participate in requirements gathering, user acceptance testing, and implementation of approved report and dashboard enhancements.
Client Data Team Collaboration
  • Work with client data contacts to clarify reporting requirements and investigate data discrepancies.
  • Assist with resolving reporting, data-transfer, and data-alignment challenges.
  • Communicate findings, open questions, and proposed resolutions clearly and professionally with internal stakeholders and client contacts.
  • Track client-facing data issues and maintain appropriate documentation of findings, root causes, and follow-up actions.
  • Escalate unresolved reporting or data risks to program leadership as appropriate.
  • Support alignment between Curant reporting outputs and client reporting expectations.