Analytics Specialist

GeorgiaTEK Systems Inc.; Blythewood (SC); On-site; USD 110,000 - 140,000; Full time

Job summary

GeorgiaTEK Systems Inc. is seeking a Specialist, Data Analytics – Technical Field Data to analyze vehicle and field data and drive quality improvements.

You will deploy AI/ML solutions, build data pipelines, and collaborate with engineering, service, warranty, and customer support teams. The role requires 5+ years of experience and a Bachelor’s in Engineering, CS, or Data Science, with expertise in Databricks, SQL, Python, AWS/Azure, and Power BI/PowerApps.

Qualifications

• Bachelor’s degree in Engineering, Computer Science, or Data Science.
• 5+ years of experience in technical data processing or analytics.
• Hands-on experience with Databricks, SQL, Python and large datasets.
• Experience deploying AI-based solutions for data processing.
• Knowledge of AI/ML, predictive analytics, and anomaly detection.
• Experience with AWS, Azure, Databricks, data warehousing, and ETL concepts.
• Experience with Power BI and PowerApps.
• Strong analytical, problem-solving, and cross-functional collaboration skills.

Responsibilities

• Analyze vehicle, field, customer, and connected vehicle data to identify emerging quality issues.
• Support end-to-end root cause analysis across vehicle systems, including powertrain, high-voltage battery, and connected features.
• Identify patterns and trends in fleet data to enable early issue detection and faster resolution.
• Develop and deploy AI/ML solutions for anomaly detection, failure prediction, and sentiment analysis.
• Analyze customer surveys, social media, web forums, call center logs, and customer feedback.
• Partner with engineering, connected vehicle, service, warranty, and customer support teams.
• Develop and maintain robust data pipelines and VIN-level Vehicle 360 traceability.
• Translate data insights into actionable engineering and product improvements.

Skills

Databricks

SQL

Python

AI/ML

Data warehousing

ETL

Power BI

PowerApps

AWS

Azure

Cross-functional collaboration

Education

Bachelor’s degree in Engineering, Computer Science, or Data Science

Tools

Databricks

Power BI

PowerApps

AWS

Azure

Job description

Specialist, Data Analytics – Technical Field Data

• Location: Blythewood, South Carolina
• Experience: 5+ years
• Education: Bachelor’s degree in Engineering, Computer Science, and/or Data Science
• Relocation Assistance: Yes
• Travel: Occasionally

Responsibilities

• Analyze vehicle, field, customer, and connected vehicle data to identify emerging quality issues.
• Support end-to-end root cause analysis across vehicle systems, including powertrain, high-voltage battery, and connected features.
• Identify patterns and trends in fleet data to enable early issue detection and faster resolution.
• Develop and deploy AI/ML solutions for anomaly detection, failure prediction, and sentiment analysis.
• Analyze customer surveys, social media, web forums, call center logs, and customer feedback.
• Partner with engineering, connected vehicle, service, warranty, and customer support teams.
• Develop and maintain robust data pipelines and VIN-level Vehicle 360 traceability.
• Translate data insights into actionable engineering and product improvements.

Required Skills

• Bachelor’s degree in Engineering, Computer Science, or Data Science.
• 5+ years of experience in technical data processing or analytics.
• Hands-on experience with Databricks, SQL, Python, and large datasets.
• Experience deploying AI-based solutions and tools for data processing.
• Knowledge of AI/ML, predictive analytics, and anomaly detection.
• Experience with AWS, Azure, Databricks, data warehousing, and ETL concepts.
• Experience with Power BI and PowerApps.
• Strong analytical, problem-solving, and cross-functional collaboration skills.

Preferred Experience

• Automotive, EV, connected vehicle, quality, warranty, or field issue analysis experience.
• Experience with telemetry, IoT, vehicle diagnostics, powertrain, or battery data.
• Experience with root cause analysis and reliability improvement.
• Experience with customer insights and Voice of Customer (VoC) analytics.