Data Analytics Specialist
Columbia, SC
Direct Placement
Up to $120k yearly
Paid Relocation Available
As a Field Monitoring Quality Specialist, you will act as a strategic partner, diving deep into vehicle and field data to identify issues that may impact customer experience and vehicle performance. Your insights will enable early detection and proactive resolution of potential concerns, helping improve product quality while strengthening customer trust and brand reputation
“In this critical role, you will help, design and implement solutions to monitor and integrate data from diverse communication channels including customer surveys, social platforms, and connected vehicle telemetry to create a comprehensive view of field performance”. We are looking for someone who thrives in complex, high-volume data environments and can uncover meaningful insights from ambiguity.
Partnering closely with engineering teams, you will play a key role in identifying product issues, guiding investigations, and ensuring teams focus on the most critical data to accelerate resolution and protect both our customers and brand reputation. Your work will have a direct impact on product development, system engineering, and the resolution of complex warranty and quality issues across our vehicle portfolio.
Key Responsibilities:
Field Issue Detection & Resolution
- Support end-to-end root cause analysis (RCA) of customer issues across full vehicle systems, including powertrain, high-voltage battery, and connected features
- Identify patterns in fleet data to enable early detection of emerging quality issues
- Drive faster resolution through data-driven insights and cross-functional collaboration
Data Strategy & Analytics:
- Define and implement strategies for collecting, organizing, and analyzing large-scale connected vehicle data
- Partner with engineering teams to establish vehicle data policies, signal strategies, and telemetry requirements
- Perform advanced data analysis to correlate vehicle behavior, software versions, and customer-reported issues
AI/ML & Advanced Analytics
- Develop and deploy AI/ML models for:
- Anomaly detection
- Failure prediction
- Sentiment analysis
- Leverage analytics to improve customer satisfaction, reliability, and warranty performance
Data Management & Integration
- Act as the bridge between software-defined vehicle data policies and real-world engineering insights
- Ensure data pipelines are robust, accurate, and actionable
- Enable a VIN-level (Vehicle 360) view for comprehensive lifecycle traceability
Cross-Functional Collaboration
- Work closely with:
- Vehicle engineering (hardware & software)
- Connected vehicle and app development teams
- Service, warranty, and customer support organizations
- Enhance data collection capabilities, user interfaces, and reporting standards across systems
Customer Insight & Voice of Customer (VoC)
- Serve as a VoC quality expert, ensuring timely and accurate feedback loops into engineering
- Design and implement customer surveys and feedback frameworks to assess product satisfaction
- Analyze large volumes of unstructured data (social media, web forums, call center logs, customer verbatims) to identify key customer pain points and trends
Qualifications:
- Education/Certifications: A bachelor’s degree in engineering, computer science and/or data science.
- Years of Experience: 5+ years in an environment related to technical data processing, preferably within a vehicle manufacturer or supplier environment. Relevant experience in other sectors will also be considered.
- Experience in automotive engineering, quality, or field issue analysis, ideally in EV or connected vehicle environments is preferred.
- Experience from non-automotive would also be acceptable with the ability to absorb meta data to perform root cause analysis.
- Hands-on experience with data analytics tools and large datasets (e.g., Databricks, SQL, Python, cloud platforms)
- Experience in running Java Script, Python, SQL, HTML/CSS
- Experience in deploying AI-based solutions and tools for data processing. Ability to build full-scale AI-powered products from scratch using available open AI
- Familiarity with AI/ML concepts and applications in anomaly detection or predictive analytics
- Understand data warehouse systems like Basic AWS or Azure data services or Databricks. Ability to support enterprise projects on as need basis.
- Ability to work across functions and translate data insights into engineering actions
- Experience with PBI and PowerApps, building app own-made solutions for data analytics.
- Strong interpersonal skills, with experience working in multicultural and team-oriented environments.
We are an EOE.
If interested, please contact
Jeena Swope