Data Scientist

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.