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- Typically 6+ years of proven experience in data science, focusing on LLMs and supervised ML models.
- Proficiency in programming languages such as Python or R, with experience in SciKit-Learn, XGBoost, Keras.
- Strong understanding of data processing and transformation techniques, including SQL and big data technologies.
- Experience developing, training, and deploying ML models and Python applications in production environments.
- Familiarity with cloud platforms like AWS Sagemaker and containerization tools like Docker and Kubernetes.
- Excellent problem-solving skills and strong communication skills.
- Build and deploy machine learning models, including propensity models and GenAI applications.
- Collaborate closely with product, program, analytics, and engineering teams to refine models.
- Leverage technical stack including Python, SQL, R, AWS, and data science libraries for AI/ML solutions.
- Utilize enterprise data sources like Salesforce and Zendesk for model development.
- Apply knowledge of LLMs to develop innovative solutions.
AWSDockerPythonSQLHadoopKerasKubernetesMachine LearningMySQLNumpySalesforceData sciencePandasSparkCommunication Skills
Posted 2024-11-20
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