Aperia Technologies develops tire management systems for commercial fleets. Its Halo platform combines automatic tire inflation with tire pressure monitoring, while Halo Connect uses machine learning to flag potential tire issues early. The company says its technology is backed by more than 100 billion miles of industry use and is designed to help fleets extend tire life, improve fuel economy, maintain vehicle uptime, and support safer operations.
Hardware Data Analyst
Analyze IoT and telematics data for Aperia Technologies’ commercial vehicle solutions. Use dashboards, modeling, and data pipelines to improve hardware reliability, performance, and customer outcomes.
Tavsif
- Build dashboards, reports, and presentations with QuickSight, Tableau, or Python libraries.
- Analyze incoming sensor and analytics data to spot trends, anomalies, and potential field issues.
- Apply statistical models and machine learning to recommend improvements to hardware reliability and performance.
- Compare firmware version outputs to verify improvements and identify regressions.
- Work with hardware engineering, product management, data science, and customer support teams.
- Provide data-based insights to address customer questions about product performance and anomalies.
- Recommend tools, methods, and processes that strengthen analysis capabilities and operational efficiency.
- Help build data pipelines for dependable ingestion, processing, and storage of large-scale field data.
- Make sure teams have the data access and tools they need to make informed decisions.
- Use field data to inform future hardware and software features.
Talablar
- Must be authorized to work in the United States on an ongoing basis without current or future employer sponsorship.
- Candidates on F-1, OPT, or STEM OPT status are not eligible.
- Bachelor’s degree in Data Science, Computer Science, or a related field.
- 2–4 years of data analysis experience; hardware-related or IoT experience is preferred.
- Proficiency in Python, SQL, MATLAB, or Excel for data analysis and modeling.
- Experience with visualization tools such as QuickSight, Tableau, Streamlit, or Looker.
- Strong understanding of statistical modeling, machine learning, and time-series data analysis.
- Experience with AWS services such as S3, Redshift, Kinesis, or IoT Core, or similar cloud platforms, is a plus.
- Strong analytical and problem-solving skills.
- Ability to turn data findings into actionable insights.
- Excellent communication skills for explaining complex data clearly to technical and non-technical stakeholders.
Imtiyozlar
- Additional compensation may include equity.
- Additional compensation may include bonuses.
- Additional compensation may include stipends.
- Medical insurance.
- Dental insurance.
- Vision insurance.
- 401(k).
- Long-term disability insurance.