Collaborate with stakeholders and data teams to identify business challenges amenable to machine learning solutions; Perform exploratory data analysis to uncover insights and transform business questions into concrete modeling tasks; Develop, optimize, and enhance machine learning algorithms and neural network architectures for natural language processing, computer vision, forecasting, and other domains; Build reliable end-to-end ML pipelines for data processing, model training, evaluation, and deployment; Continuously monitor, retrain, and update models to maintain predictive accuracy; Operationalize and serve models at scale using containers, orchestration, and cloud infrastructure
Requirements:
Have a B.Tech/M.Tech or equivalent in Computer Science, Statistics, Mathematics, or related quantitative field or equivalent experience; Have 8+ years of professional experience developing and deploying machine learning models and pipelines at scale; Self-starter who can take initiative, drive consensus, and mentor junior team members; Strong software engineering skills and experience developing in languages like Python, R, and Scala; Experience with statistical and machine learning theory, algorithms, and frameworks like SciKit-Learn, PyTorch, TensorFlow
Text:
Principal Data Scientist Collaborate with stakeholders and data teams to identify business challenges amenable to machine learning solutions; Perform exploratory data analysis to uncover insights and transform business questions into concrete modeling tasks; Develop, optimize, and enhance machine learning algorithms and neural network architectures for natural language processing, computer vision, forecasting, and other domains; Build reliable end-to-end ML pipelines for data processing, model training, evaluation, and deployment; Continuously monitor, retrain, and update models to maintain predictive accuracy; Operationalize and serve models at scale using containers, orchestration, and cloud infrastructure Have a B.Tech/M.Tech or equivalent in Computer Science, Statistics, Mathematics, or related quantitative field or equivalent experience; Have 8+ years of professional experience developing and deploying machine learning models and pipelines at scale; Self-starter who can take initiative, drive consensus, and mentor junior team members; Strong software engineering skills and experience developing in languages like Python, R, and Scala; Experience with statistical and machine learning theory, algorithms, and frameworks like SciKit-Learn, PyTorch, TensorFlow
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