Data Analyst - EV Charging Reliability & Fault Analytics
Listed on 2026-01-08
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IT/Tech
Data Analyst
Location: California
About Us
Charger Help! Inc., a California-based tech company, offers impactful solutions that power-up the EV ecosystem by providing Reliability as a Service (RaaS), data-driven insights via our EMPWR platform, and Learning & Development to prepare the next generation of EVSE technicians. We pride ourselves on being a trusted partner within our industry.
In the EVSE landscape, we’re not just solving a challenge; we’re driving the charge towards a sustainable future. Our mission is crystal clear: maximizing EV charging station uptime to unlock the full potential of mass EV adoption. Through innovation, integrity, and an unwavering commitment to quality and safety, we foster a culture of excellence and trust. If you join us you’ll be part of a dynamic team that’s leading EV reliability.
Together, we’re not just changing the industry; we’re helping shape the future of transportation and environmental sustainability.
We are seeking a skilled Contract Data Analyst to support a high-priority analytics project focused on EV charging reliability and fault performance. This role will play a critical part in transforming contributor and operational data into meaningful insights that support product health dashboards, EVSE OEM design robustness, and industry-facing reporting.
You will work with aggregated datasets from multiple industry partners, producing statistical analysis and visualizations that strengthen both technical decision-making and written narratives. This is a fast-turnaround project requiring immediate availability and the ability to deliver high-quality analysis on a tight timeline.
What You’ll Do Data Extraction & Normalization- Extract and normalize fault data from an existing database, with a focus on:
- EVSE-specific charge failures
- Hardware and software faults
- Associated error codes and failure modes
- Clean, validate, and organize datasets from multiple contributors and partners.
- Standardize diverse data sources into a unified, analysis-ready format.
- Perform statistical analysis on fault occurrence, including:
- Frequency analysis
- Histograms and distributions
- High-occurrence and repeat-failure patterns
- Analyze fault location and attribution, distinguishing issues related to:
- EVSE hardware
- EV-side issues
- Customer/user behavior
- Back-office systems (e.g., payment authorization, network communication)
- Deliver technical insights related to EVSE design robustness and reliability trends relevant to OEMs.
- Identify key trends impacting EV charger uptime and driver experience.
- Produce data reports and summaries highlighting common field faults and systemic issues.
- Create clear, compelling visualizations (charts, tables, dashboards) for inclusion in:
- Product health dashboards
- Industry and research-style reports
- Collaborate with a writing team by:
- Providing analytical context
- Ensuring methodology aligns with the report outline
- Strengthening the narrative with data-backed insights
Required Qualifications
- Proven experience as a Data Analyst, preferably in technical, operational, or infrastructure-focused domains.
- Strong skills in data cleaning, normalization, and statistical analysis.
- Experience creating clear, publication-ready visualizations.
- Ability to synthesize complex datasets into actionable insights for both technical and non-technical audiences.
- Comfortable working independently under tight timelines and delivering results quickly.
- Familiarity with EV charging infrastructure, clean energy, or transportation datasets.
- Experience supporting industry reports, research publications, or product health dashboards.
- Understanding of fault classification, reliability engineering, or systems diagnostics.
- Immediate start required
- Must have availability to complete the project over the next couple of weeks
- This is a short-term, contract-based engagement with a clearly defined scope and deliverables.
- Provide aggregated fault analytics focused on high-occurrence EV charging issues.
- Expand coverage of common field faults for product health dashboards.
- Generate actionable technical insights related to EVSE design robustness, fault attribution, and driver experience.
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