Job Description

Responsibilities:

Develop and maintain data visualization dashboards using Grafana to monitor and analyze hardware performance metrics.
Automate scripts written by engineers to streamline data collection and processing workflows.
Create tools to extract and transform data from data lakes, ensuring data integrity and accessibility.
Apply AI/ML techniques to analyze large datasets, identify patterns, and generate actionable insights to improve hardware performance and reliability.
Collaborate with cross-functional teams, including hardware engineers, software developers, and data analysts, to understand data requirements and deliver solutions.
Conduct exploratory data analysis to uncover trends and anomalies in hardware data.
Develop predictive models to forecast hardware failures and optimize maintenance schedules.
Document methodologies, processes, and findings to ensure knowledge sharing and reproducibility.

Qualifications:

Bachelor’s or Master’s degree in Data Science, Computer Science, Electrical Engineering, or a related field.
Proven experience with Grafana for data visualization and monitoring.
Proficiency in scripting languages such as Python, Bash, or similar for automating tasks.
Experience in creating tools to pull and process data from data lakes (e.g., AWS S3, Azure Data Lake).
Strong background in AI/ML techniques and their application to large datasets.
Familiarity with hardware performance metrics and data analysis.
Excellent problem-solving skills and attention to detail.
Strong communication skills and ability to work collaboratively in a team environment.

Preferred Qualifications:

Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Knowledge of satellite communication systems and hardware.
Experience with big data technologies such as Hadoop, Spark, or similar.
Familiarity with version control systems like Git.
Familiarity with RF performance measurements such as power, EVM, Noise Figure, ACPR, and ACLE.

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