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Mid-level ML role in Bangalore at a known mid-tier employer with broad required skillset, high applicant density.
Model-building and deployment skills transfer broadly across industries, though recommendation-system expertise favors certain domains.
Explicit 4–6 years requirement plus many mandatory ML, deployment, and statistical tool proficiencies increases filter strictness.
Develop and implement Next Best Offer models and advanced machine learning solutions to drive business objectives and enhance customer engagement.
Build, validate, and optimize machine learning models using Python, PySpark, and R for accuracy and reliability, including automation of pipelines using KubeFlow and BentoML.
Apply statistical analyses and monitoring tools (SAS, SPSS, R Studio) to extract insights, maintain model performance, and recommend improvements.
4 to 6 years of experience in advanced data science roles with hands-on machine learning and statistical modeling.
Proficiency in Python, PySpark, SAS, SPSS, R, and experience with probabilistic graph models, regression, forecasting, decision trees, and SVM algorithms.
Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative discipline.
Not explicitly mentioned in the JD: notice period, location, or specific regulatory requirements.
Experienced in production-level machine learning model deployment and automation using tools like KubeFlow and BentoML, indicating strong operational expertise.
Skilled in both statistical analysis and machine learning with knowledge of advanced algorithms and ensemble methods, suitable for complex business challenges.
Ability to translate business requirements into data science solutions with experience in recommendation systems, personalization algorithms, and experimental design (A/B testing).