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Job Description
Structured overview of role & requirementsAbout This Role
Design and implement advanced statistical models and machine learning algorithms delivering actionable business insights.
Develop, train, and deploy scalable predictive and classification models using ML frameworks (e.g., TensorFlow, PyTorch) and manage model lifecycle in production.
Perform comprehensive statistical analysis and data validation to ensure high data quality and support data-driven decision-making.
Minimum Requirements
4 to 6 years of hands-on experience in advanced data science roles involving statistical analysis and machine learning.
Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline.
Proficient programming skills in Python and PySpark, with advanced statistical knowledge (hypothesis testing, regression analysis).
Experience with machine learning frameworks (TensorFlow, PyTorch, Sci-Kit Learn, etc.) and statistical software (SAS, SPSS, R).
Ideal Candidate Profile
Experienced in building and deploying machine learning models at scale with knowledge of production deployment tools like KubeFlow and BentoML.
Strong statistical modeling background including time series forecasting, probabilistic graph models, and advanced regression techniques.
Familiarity with cloud-based data science platforms (AWS SageMaker, Azure ML, or Google Cloud AI Platform) and advanced data validation tools (Great Expectations, Evidently AI).