Hardware Data Analyst - Remote

Lime Rock New Energy; United States; Remote; USD 95,000 - 123,000; Full time

Benefits offered by this job

Equity

Bonuses

Medical insurance

Dental insurance

Vision insurance

401(k)

Job summary

Aperia seeks a Hardware Data Analyst in the United States to harness data from telematics and IoT devices, impacting hardware performance, reliability, and efficiency.

You will design dashboards with QuickSight/Tableau, monitor sensor data, apply ML and time-series models, and compare firmware outputs to drive improvements and inform product decisions.

Qualifications

• Bachelor's degree in Data Science, Computer Science, or related field.
• 2–4 years of experience in data analysis, with exposure to hardware or IoT systems preferred.
• Proficiency in Python, SQL, MATLAB, or Excel for data analysis and modeling.
• Experience with visualization tools like QuickSight, Tableau, Streamlit, or Looker.
• Strong understanding of statistics, ML, and time-series data analysis.
• Experience with AWS or similar cloud platforms is a plus.

Responsibilities

• Design and deliver dashboards using QuickSight/Tableau/Plotly to visualize performance metrics.
• Monitor and analyze sensor data to identify trends, anomalies, and issues.
• Apply statistical models and ML to extract insights andRecommend improvements for hardware reliability and performance.
• Compare outputs from firmware versions to validate changes.
• Collaborate with hardware engineers, PMs, and data scientists on data analysis strategies.
• Provide data-driven insights to support customer support and product decisions.
• Propose new tools/processes to enhance data analysis and efficiency.
• Design data pipelines for large-scale field data ingestion and processing.
• Act as data advocate ensuring accessible data for teams.
• Incorporate field data into future hardware and software features.

Skills

Python

SQL

MATLAB

Excel

Time-series analysis

Statistical modeling

Machine learning

Strong communication

Problem solving

Education

Bachelor's degree in Data Science or related field

Tools

QuickSight

Tableau

Streamlit

Looker

AWS

Job description

Aperia is unlocking a new era of efficiency and sustainability for commercial vehicle fleets, by developing innovative hardware and data analytics solutions. Inventors of the award-winning and disruptive Halo(tm) Automatic Tire Inflator, and the cloud delivered Halo Connect tire analytics platform. Aperia saves fleets thousands of hours of down-time every week, reduces the carbon footprint and environmental impact of the freight industry. Join us as we expand our product offering and take the next steps on our journey toward bringing the "backbone of our economy" into the automation age.

This position requires candidates to be authorized to work in the US on an ongoing basis without current or future employer sponsorship. We are unable to sponsor or transfer H-1B or other employment-based visas, and candidates currently on F-1, OPT, STEM OPT status are not eligible for this role.

Your Role

As a Hardware Data Analyst, you will harness vast amounts of data streaming from our extensive deployment of telematics and IoT devices in the field. Your work will directly impact our hardware systems' performance, reliability, and efficiency, helping deliver exceptional customer experiences. Collaborating with engineering, product management, data science, and customer support teams, you will process and analyze sensor and analytics data to uncover insights, identify issues, and drive continuous improvement.

Your Responsibilities

• Design and deliver dashboards, reports, and presentations using tools like QuickSight, Tableau, or Python libraries to visualize performance metrics and communicate findings effectively.
• Continuously monitor and analyze incoming sensor and analytics data to identify trends, anomalies, and potential issues in the field.
• Use statistical models and machine learning techniques to extract insights and generate actionable recommendations for hardware reliability and performance improvements.
• Compare outputs from various firmware versions to validate improvements or detect unexpected regressions.
• Collaborate with hardware engineers, product managers, and data scientists to define and execute data analysis strategies.
• Support customer support teams by providing data-driven insights to address product performance and anomaly-related inquiries.
• Proactively identify and propose new tools, methods, or processes to enhance data analysis capabilities and improve operational efficiency.
• Collaborate with the engineering and data science teams to design and implement data pipelines that ensure reliable ingestion, processing, and storage of large-scale field data.
• Act as a data advocate within the organization, ensuring teams have the necessary data access and tools to make informed decisions.
• Collaborate with product development teams to ensure field data is incorporated into the design of future hardware and software features.

Skills/Qualifications

• Bachelor’s degree in Data Science, Computer Science, or a related field.
• 2-4 years of experience in data analysis, with exposure to hardware-related roles or IoT systems preferred.
• Proficiency in Python, SQL, MATLAB, or Excel for data analysis and modeling.
• Demonstrated experience with visualization tools like Quicksight, Tableau, Streamlit, or Looker.
• Strong understanding of statistical modeling, machine learning, and time-series data analysis.
• Experience with cloud platforms like AWS (S3, Redshift, Kinesis, IoT Core) or similar is a plus.
• Strong problem-solving and analytical skills, with the ability to translate data findings into actionable insights.
• Excellent communication skills to present complex data in a clear, concise manner to technical and non-technical stakeholders.

Pay Range: $95,000 - $123,000

*Base salary only. Salary is dependent on multiple factors including, but not limited to, experience and location.

**Additional compensation may include equity, bonuses, stipends, medical, dental, vision, 401(k), and long-term disability insurance.