Responsibilities

• Develop and implement machine learning models to solve complex business problems and enhance decision-making processes.
• Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows.
• Utilize Azure Open AI Service and Cloud AutoML to streamline model deployment and scalability.
• Conduct exploratory data analysis (EDA) to uncover trends and patterns that inform strategic initiatives.
• Design and maintain data pipelines using Airflow to ensure efficient data processing and management.
• Apply knowledge graph techniques to enhance data connectivity and retrieval.
• Implement MLOps practices to automate and optimize the machine learning lifecycle.
• Leverage OpenCV and deep learning frameworks like TensorFlow and PyTorch for computer vision projects.
• Develop AI-enabled chatbots using Dialogflow and natural language processing techniques.
• Utilize R Statistical Package and Python for data manipulation and statistical analysis.
• Optimize search engine performance through data-driven SEO strategies.
• Provide insights and recommendations to improve asset and wealth management processes.
• Stay updated with the latest advancements in AI and machine learning to continuously improve solutions.


 

Qualifications

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• Possess strong technical skills in statistics machine learning and artificial intelligence.
• Demonstrate proficiency in cloud-based services such as Azure Open AI and Cloud AutoML.
• Exhibit expertise in data analysis tools like EDA and R Statistical Package.
• Have experience with AI frameworks including TensorFlow PyTorch and OpenCV.
• Show capability in developing AI chatbots and natural language processing applications.
• Understand the domain of cards and payments and asset and wealth management.
  • Be skilled in programming languages such as Python for data science applications.