Opportunity with Fractal For AI/ML & Visualization

Role Summary Develop analytical models and supporting data pipelines that identify potential Open Main conditions using AMI, network topology, and asset data. Support model development, validation, and operationalization activities. Key Responsibilities Perform exploratory analysis of AMI and network datasets. Engineer features from Customer interval usage Voltage readings Transformer relationships Network topology Asset metadata Develop and test classification models under the guidance of the Lead Data Scientist. Support graph construction and graph feature generation for network-based analytics. Analyze model performance and investigate false positives and false negatives. Build datasets required for training, validation, and testing. Create visualizations and analytical summaries to support engineering review. Document model logic, assumptions, and results. Participate in model deployment and monitoring activities. Qualifications Bachelor's or Master's degree in Data Science, Statistics, Engineering, Computer Science, or related field. 5-8 years of experience in machine learning or advanced analytics. Experience with Supervised classification techniques Feature engineering Time-series analysis Anomaly detection Graph analytics concepts Proficiency in Python SQL Data visualization tools Experience working with large-scale utility, IoT, sensor, or operational datasets preferred. Preferred Technical Skills Random Forest XGBoost Gradient Boosting Graph Neural Networks (preferred) NetworkX or similar graph analytics libraries Time-series feature extraction Model explainability techniques (SHAP, feature importance, etc.) Intrested candidate can apply at payal.singh@fractal.ai Only immediate joiners to apply. .