DE&A - AIML - Data Science - Machine Learning

Analyst – Data Science 3-8 yrs

• Design and implement machine learning pipelines that curate datasets, train, test, and validate models, and deploy them into production.
• Utilize LLMs and Generative AI techniques to enhance data analysis, natural language processing, and predictive modeling capabilities.
• Apply supervised, unsupervised, and deep learning techniques to address business challenges, including the development of recommendation engines and scoring systems.
• Conduct A/B testing and utilize statistical techniques to evaluate model performance and improve outcomes.
• Collaborate with cross-functional teams to integrate machine learning solutions into existing systems and processes.
• Proficient in model building using R or Python, with a strong focus on data mining and leveraging large datasets.
• Demonstrated ability to design and build machine learning pipelines, including model training, validation, and deployment.
• Deep understanding of statistical and machine learning modeling, with experience applying these techniques to real-world business problems.
• Hands-on experience with analytics and big data technologies, particularly within Microsoft Azure, including Azure Machine Learning, Azure Cognitive Services, and Azure Databricks.
• Working knowledge of machine learning frameworks and tools such as scikit-learn, TensorFlow, PyTorch, and ONNX.
• Experience with LLMs and Generative AI frameworks, including fine-tuning and deploying models for specific applications.
• Experience with cloud service machine learning platforms, preferably Azure, and setting up data and experimental platforms.
• Extensive knowledge of model management, ideally using Azure ML service and/or ML Flow, as well as deployment using Azure Kubernetes Service.