Teams at PSignite

Build and maintain end-to-end machine learning pipelines for forecasting, including data ingestion, feature engineering, training, evaluation, deployment, monitoring, and serving. Train gradient boosting and deep learning models, manage cloud workloads on AWS, containerize services, and implement testing, versioning, reproducibility, and CI/CD practices. Collaborate with data scientists and stakeholders to productionize analytical solutions.

Build and deploy scalable machine learning models for sales forecasting, promotion effectiveness, pricing analysis, and price elasticity. Responsibilities include feature engineering, time-series modeling, hyperparameter optimization, model evaluation, MLOps, explainable AI, data quality assurance, and independent research. The role partners with technical and business stakeholders to communicate analytical insights and supports production-grade machine learning pipelines in a fully remote environment.