Job
Description
Experience: 5-6 years Key Responsibilities Process, analyze, and interpret time-series data from MEMS sensors (e.g., accelerometers, gyroscopes, pressure sensors). Develop and apply statistical methods to identify trends, anomalies, and key performance metrics. Compute and optimize KPIs related to sensor performance, reliability, and drift analysis. Utilize MATLAB toolboxes (e.g., Data Cleaner, Ground Truth Labeler) or Python libraries for data validation, annotation, and anomaly detection. Clean, preprocess, and visualize large datasets to uncover actionable insights. Collaborate with hardware engineers, software developers, and product owners to support end-to-end data workflows. Convert and format data into standardized schemas for use in data pipelines and simulations. Generate automated reports and build dashboards using Power BI or Tableau. Document methodologies, processes, and findings in clear and concise technical reports. Required Qualifications Proficiency in Python or MATLAB for data analysis, visualization, and reporting. Strong foundation in time-series analysis , signal processing, and statistical modeling (e.g., autocorrelation, moving averages, seasonal decomposition). Experience working with MEMS sensors and sensor data acquisition systems. Hands-on experience with pandas, NumPy, SciPy, scikit-learn, and matplotlib . Ability to develop automated KPI reports and interactive dashboards (Power BI or Tableau). Preferred Qualifications Prior experience with data from smartphones, hearables, or wearable devices . Advanced knowledge in MEMS sensor data wrangling techniques. Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform. Exposure to real-time data streaming and processing frameworks/toolboxes. Show more Show less
