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Mid-level ML role in Bangalore with common Data Scientist title and broad skillset increases competition.
Specialized ML model development, probabilistic graphs, and MLOps tools require domain-specific background.
Explicit 4-6 years plus many mandatory ML, deployment and statistical tool requirements tightens shortlisting.
Develop and implement Next Best Offer models and advanced machine learning solutions to drive business outcomes and enhance customer engagement.
Build, validate, and optimize machine learning models using Python, PySpark, and R, ensuring scalability via KubeFlow and BentoML.
Conduct comprehensive statistical analyses using SAS, SPSS, and R Studio, and monitor model performance to recommend improvements.
4 to 6 years of experience in advanced data science roles with hands-on ML and statistical modeling.
Proficiency in Python, PySpark, R, SAS, SPSS, and machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, Keras).
Experience with probabilistic graph models, regression methods, classification algorithms (decision trees, SVM), and forecasting techniques (ARIMA, exponential smoothing).
Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science or a related quantitative field.
Experienced in developing scalable ML pipelines and deploying models in cloud environments using tools like KubeFlow and BentoML.
Skilled in statistical hypothesis testing, model validation, and monitoring using tools such as Great Expectations and Evidently AI.
Familiar with recommendation systems, A/B testing, experimental design, and advanced ensemble and boosting algorithms.