We are seeking a Signal Processing & Data Analyst to support data-driven engineering and analytics activities within our technical training ecosystem. The role focuses on analyzing structured datasets, including sensor-based and simulated engineering data, to generate meaningful insights and support applied learning modules.
Key Responsibilities
• Process and analyze sensor-based and simulated engineering datasets to identify patterns, trends, and anomalies
• Apply basic signal processing concepts such as filtering, smoothing, and noise reduction on structured datasets
• Perform data cleaning, transformation, and statistical analysis using Python (Pandas, NumPy) and Excel
• Develop data visualizations and summary reports to communicate analytical findings
• Support creation of engineering-based case studies and training datasets for internal use
• Assist in designing simulation-based datasets that replicate real-world engineering scenarios
• Collaborate with internal teams to ensure data accuracy, consistency, and usability
• Document workflows, methods, and results for internal reference and training support
Required Qualifications
• Bachelor’s or Master’s degree in Electrical Engineering, Electronics, Computer Engineering, or related field
• Basic understanding of:
• Data analysis concepts
• Signals or sensor data interpretation
• Statistical methods
• Familiarity with Python, Excel, or similar tools
Preferred Qualifications
• Exposure to sensor data or engineering datasets
• Basic understanding of signal processing or DSP concepts
• Experience with data visualization tools
Work Details
• Type: Internship / Entry-level role
• Hours: Minimum 20 hours per week
• Location: [Onsite/Remote/Hybrid]
