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Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and deploy robust statistical and machine learning models to generate actionable business insights.
Conduct advanced statistical analysis and forecasting using Python, PySpark, R, SAS, and SPSS across large-scale data sets.
Manage model lifecycle including deployment and monitoring using ML frameworks and production tools like TensorFlow, PyTorch, KubeFlow, and BentoML.
Minimum Requirements
4 to 6 years of hands-on experience in data science roles focusing on statistical analysis and machine learning.
Proficient in Python, PySpark, R, SAS, SPSS and experienced in ML frameworks such as TensorFlow, PyTorch, Sci-Kit Learn.
Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or closely related field.
Certification in Data Science or Machine Learning from recognized institutions preferred (e.g., Microsoft Azure Data Scientist Associate, TensorFlow Developer Certificate).
Ideal Candidate Profile
Experienced in applying advanced hypothesis testing, regression, and time series forecasting techniques in business contexts.
Capable of managing full cycle model deployment and validation using modern ML tools and frameworks in production environments.
Strong background in statistical software and programming, with demonstrated ability to translate complex data findings into business-driving insights.