Data Scientist- Time Series

As a skilled Data Scientist at Presage Insights, your role will involve focusing on developing advanced anomaly detection and fault diagnostic models using time series data. You will be responsible for the following key responsibilities: - **Data Analysis & Preprocessing:** - Collect, clean, and preprocess time series data from sensors, including vibration and acoustic sources. - Apply signal processing techniques (e.g., FFT, STFT, MFCC) to extract meaningful features from raw data. - **Model Development:** - Design and implement ML/DL models for anomaly detection and fault diagnosis (e.g., Isolation Forest, One-Class SVM, LSTM Autoencoders). - Develop multimodal models that integrate acoustic and vibration data for improved fault detection accuracy. - **Performance Evaluation:** - Evaluate model performance using appropriate metrics and refine models to enhance accuracy and reliability. - Conduct experiments and A/B tests to validate model effectiveness. - **Collaboration & Communication:** - Work closely with cross-functional teams, including engineering and maintenance, to understand requirements and implement solutions. - Present findings and insights to stakeholders through reports and visualizations. As for the qualifications required for this role: - **Education:** - Bachelors or Masters degree in Computer Science, Electrical Engineering, Data Science, or a related field. - **Experience:** - Proven experience in developing anomaly detection and fault diagnostic models using time series data. - Hands-on experience with vibration and acoustic data analysis. - Familiarity with signal processing techniques and tools. - Experience with ML/DL frameworks such as TensorFlow, PyTorch, or scikit-learn. - **Skills:** - Proficiency in programming languages like Python or R. - Strong analytical and problem-solving skills. - Excellent communication and collaboration abilities. In addition to the qualifications, the company prefers candidates with experience in real-time data processing, edge computing, IoT platforms, sensor data integration, and familiarity with cloud services such as AWS, Azure, or GCP. As a skilled Data Scientist at Presage Insights, your role will involve focusing on developing advanced anomaly detection and fault diagnostic models using time series data. You will be responsible for the following key responsibilities: - **Data Analysis & Preprocessing:** - Collect, clean, and preprocess time series data from sensors, including vibration and acoustic sources. - Apply signal processing techniques (e.g., FFT, STFT, MFCC) to extract meaningful features from raw data. - **Model Development:** - Design and implement ML/DL models for anomaly detection and fault diagnosis (e.g., Isolation Forest, One-Class SVM, LSTM Autoencoders). - Develop multimodal models that integrate acoustic and vibration data for improved fault detection accuracy. - **Performance Evaluation:** - Evaluate model performance using appropriate metrics and refine models to enhance accuracy and reliability. - Conduct experiments and A/B tests to validate model effectiveness. - **Collaboration & Communication:** - Work closely with cross-functional teams, including engineering and maintenance, to understand requirements and implement solutions. - Present findings and insights to stakeholders through reports and visualizations. As for the qualifications required for this role: - **Education:** - Bachelors or Masters degree in Computer Science, Electrical Engineering, Data Science, or a related field. - **Experience:** - Proven experience in developing anomaly detection and fault diagnostic models using time series data. - Hands-on experience with vibration and acoustic data analysis. - Familiarity with signal processing techniques and tools. - Experience with ML/DL frameworks such as TensorFlow, PyTorch, or scikit-learn. - **Skills:** - Proficiency in programming languages like Python or R. - Strong analytical and problem-solving skills. - Excellent communication and collaboration abilities. In addition to the qualifications, the company prefers candidates with experience in real-time data processing, edge computing, IoT platforms, sensor data integration, and familiarity with cloud services such as AWS, Azure, or GCP.